data systems engineer

<div><p><b>Title:</b></p>
Big Data Systems Engineer<p></p><p><b>
Belong, Connect, Grow, with KBR!</b></p><p>
KBR&rsquo;s National Security Solutions (NSS) team provides high-end engineering and advanced technology solutions to our customers in the intelligence and national security communities. In this position, your work will have a profound impact on the country&rsquo;s most critical role &ndash; protecting our national security.</p><p></p><p>
KBR is seeking a Big Data Systems Engineer to join our team. The successful candidate will be part of the KBR team supporting the Test Resource Management Center&rsquo;s (TRMC) Big Data (BD) and Knowledge Management (KM) Team deploying BD and KM systems for DoD testing Ranges and various acquisition programs.</p><p></p><p><b>
Responsibilities:
</b></p><ul><li>The Big Data Systems Engineer will work on the deployment and integration of a highly visible data analytic project called Cloud Hybrid Edge-to-Enterprise Evaluation Test &amp; Analysis Suite (CHEETAS) at multiple DoD ranges and labs.</li><li>
As a Big Data Systems Engineer, you will be a critical part of our technical team responsible for deploying CHEETAS within customer environments. You will be the frontline interface that customers will have when first experiencing CHEETAS within their DoD Range and lab environments.</li><li>
This position will require you to work closely with system administrators and software developers to communicate, document and ultimately resolve deployment issues as they arise.</li><li>
You will deploy CHEETAS within disparate DoD testing Ranges and acquisition programs environments (on different non-standard hardware stacks and integrated into different existing ecosystems) sometimes located within DoD vaults with no outside internet connectivity.</li><li>
Work on the deployment and integration of a highly visible data analytic project called Cloud Hybrid Edge-to-Enterprise Evaluation Test &amp; Analysis Suite (CHEETAS) at multiple DoD ranges and labs</li><li>
Deploy CHEETAS within customer environments</li><li>
Work closely with system administrators and software developers to communicate, document and ultimately resolve deployment issues as they arise</li><li>
Deploy CHEETAS within disparate DoD testing Ranges and acquisition programs environments (on different non-standard hardware stacks and integrated into different existing ecosystems) sometimes located within DoD vaults with no outside internet connectivity</li></ul><p></p><p><b>
Work Environment:
</b></p><ul><li><b>Location:</b> Remote - The candidate can either work in one of KBR&rsquo;s facilities or work from home, with a stable internet connection.</li><li><b>
Travel Requirements:</b> This position is anticipated to require travel of 25% with surges possible up to 50% to support end users located at various DoD Ranges and Labs across the US (including Alaska and Hawaii).</li><li><b>
Working Hours:</b> Standard</li></ul><p></p><p><b>
Basic Qualifications/Knowledge:</b></p><ul><li>
Must have an active TS/SCI Security Clearance to be considered for this position.</li><li>
This position requires a bachelor's degree in a STEM Computer Science, Data Science, Statistics or related, technical field, and 10 years of DoD experience. <b>Entry level Big Data Engineers will NOT be considered due to the breadth of knowledge necessary to be successful in the position.</b></li><li>
Previous experience must include three (3) years of hands-on experience in the integration with and configuration of: SQL Server Big Data Cluster, CentOS, Ubuntu, RedHat, Windows Server, VMWare, etc.)</li><li>
Previous experience must include five (5) years of hands-on experience in big data environments.</li><li>
Must be adept at deploying and configuring Big Data and Knowledge Management tools in an enterprise environment.</li><li>
Must have extensive technical expertise in the configuration and troubleshooting of big data ecosystems.</li><li>
Must have excellent written and verbal communication skills and be comfortable assisting customers with installation and configuration of their big data infrastructure.</li><li>
Must have strong troubleshooting skills and the ability to become a CHEETAS deployment subject matter expert.</li><li>
Must be comfortable working with a wide range of stakeholders and functional teams at various levels of experience.</li><li>
Excellent interpersonal skills, oral and written communication skills, and strong personal motivation are necessary to succeed within this position.</li><li>
Experience with installation, configuration, integration with and usage of the following tools and technologies: NFS, SMB, S3, SQL Server, Windows Server, Windows 10/11, Linux (CentOS, Ubuntu, RedHat).</li><li>
Must be prepared to learn new business processes or CHEETAS application nuances every Agile sprint release (roughly every 6 weeks) prior to deploying to customer sites.</li><li>
Ability to problem solve, debug, and troubleshoot while under pressure and time constraints is required.</li><li>
Ability to communicate effectively about technical topics to both experts and non-experts at both the management and technical level is required.</li><li>
Ability to work independently and provide appropriate recommendations for optimal design, analysis, and development.</li><li>
Excellent verbal communications skills are required, as the Integration Engineer will be in frequent contact with the project technical lead, be taking direction from various government leads, and will frequently be interacting with end users to gather requirements and implement solutions while away from other team members.</li><li>
Excellent testing, debugging and problem-solving skills are required to be successful in this position.</li><li>
Experience designing, building, integrating with and maintaining both new and existing big data systems and solutions.</li><li>
Ability to speak and present findings in front of large groups.</li><li>
Ability to document and repeat procedures.</li><li>
This position is anticipated to require travel of 25% with surges possible up to 50% to support end users located at various DoD Ranges and Labs across the United States.</li></ul><p></p><p><b>
Preferred Qualifications:
</b></p><ul><li>Experience working in government/defense labs and their computing restrictions.</li><li>
Experience working with major DoD acquisition programs.</li><li>
Knowledge of the Test and Training Enabling Architecture (TENA), the Joint Mission Environment Testing Capability (JMETC) and distributed testing and training.</li><li>
Experience with working in distributed team environment.</li><li>
Ability to teach and mentor engineers with a variety of skill levels and backgrounds.</li><li>
Knowledge of DoD cybersecurity policies.</li></ul><p></p><p><b>
Basic Compensation:
</b></p><p><b>$142,400 - $180,000 (For the Denver, CO Area only)</b></p><p><b>
$148,900 - $200,000 (For the Los Angeles, CA Area Only)</b></p><p><b>
$148,900 - $200,00 (For the Washington, DC Area Only)</b></p><p></p><p>
The offered rate will be based on the selected candidate&rsquo;s working location, knowledge, skills, abilities and/or experience, clearance level, contract affordability and in consideration of internal parity.</p><p></p><p><b>
Additional Compensation:</b></p><p>
KBR may offer bonuses, commissions, or other forms of compensation to certain job titles or levels, per internal policy or contractual designation. Additional compensation may be in the form of a sign on bonus, relocation benefits, short-term incentives, long-term incentives, or discretionary payments for exceptional performance.</p><p></p><p>
Belong, Connect and Grow at KBR<br>
<br>
At KBR, we are passionate about our people and our Zero Harm culture. These inform all that we do and are at the heart of our commitment to, and ongoing journey toward being a People First company. That commitment is central to our team of team&rsquo;s philosophy and fosters an environment where everyone can Belong, Connect and Grow. We Deliver &ndash; Together.</p><p></p><p>
KBR is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.</p></div><p></p>

Big Data Systems Engineer

astrocaria

<p>Position Overview</p><p>Astrocaria is seeking a <b>Ground Data Systems Engineer</b> to support the architecture, integration, and operational deployment of next-generation <b>Ground Data Systems (GDS)</b> supporting spacecraft missions.</p><p>This early-career systems engineering role supports the integration, verification, and operation of <b>voice, video, telemetry, and command systems</b> that enable spacecraft operations and mission data delivery. The engineer will work closely with spacecraft, flight software, mission operations, and infrastructure teams to ensure reliable data flows between spacecraft and mission control environments.</p><p>This position contributes to the design, modernization, and operational support of ground data infrastructure supporting current and future space missions, including human spaceflight and deep space exploration programs.</p><p>You will be part of a team helping develop the ground systems that enable the next generation of space exploration missions.</p><p>ResponsibilitiesSystems Engineering &amp; Integration</p><ul><li>Support <b>requirements development, baselining, verification, and validation</b> for Ground Data Systems.</li><li>Assist in defining and refining <b>interfaces between spacecraft systems and ground infrastructure</b>.</li><li>Support system integration and test activities for telemetry, command, voice, and video data systems.</li><li>Participate in system architecture discussions and engineering reviews.</li></ul><p>Ground System Operations</p><ul><li>Develop and maintain <b>Ground Data System operational procedures</b> for integration, checkout, and mission operations.</li><li>Support operational activities including <b>real-time telemetry monitoring, command execution, and data management</b>.</li><li>Assist mission operations teams during testing and mission events.</li></ul><p>Software &amp; Data Systems Support</p><ul><li>Support deployment and integration of <b>ground software tools and mission data systems</b>.</li><li>Assist in maintaining data flow pipelines, command generation tools, telemetry databases, and mission analysis tools.</li><li>Collaborate with system administrators to troubleshoot issues related to <b>hardware, operating systems, networks, and data systems</b>.</li></ul><p>Mission Support</p><ul><li>Support on-console and on-call operational activities during mission testing and critical mission phases.</li><li>Travel to mission support facilities when required (less than 25%).</li></ul><p>Innovation &amp; Process Improvement</p><ul><li>Identify opportunities to integrate <b>automation, AI, and advanced analytics</b> into systems engineering and mission operations workflows.</li><li>Support modernization of legacy ground systems and integration of emerging mission technologies.</li></ul><p>Basic Qualifications</p><ul><li>Bachelor&rsquo;s degree in <b>Aerospace Engineering, Systems Engineering, Computer Engineering, Computer Science, or related field</b></li><li>Experience or familiarity with <b>systems engineering processes</b>, including requirements development, verification, and validation</li><li>Experience working in <b>Linux environments</b> with basic Unix commands and utilities</li><li>Strong written and verbal communication skills</li><li>Ability to work collaboratively with engineering teams and mission operators</li><li>Strong analytical and problem-solving skills</li><li>Ability to work independently in a fast-paced technical environment</li><li><b>U.S. Citizenship required</b></li></ul><p>Preferred Qualifications</p><ul><li>Experience working in <b>Agile/Scrum development environments</b></li><li>Experience with <b>automation frameworks or system test automation</b></li><li>Experience with requirements management tools such as <b>DOORS or Cradle</b></li><li>Experience with <b>Python scripting or software development in Linux environments</b></li><li>Familiarity with <b>spacecraft telemetry, command systems, and mission operations</b></li><li>Experience supporting <b>space mission ground systems</b></li><li>Experience working with <b>NASA mission environments or government space programs</b></li></ul><p>Job Type: Full-time</p><p>Pay: $60,000.00 - $210,000.00 per year</p><p>Benefits:</p><ul><li>Dental insurance</li><li>Health insurance</li><li>Paid time off</li><li>Vision insurance</li></ul><p>Application Question(s):</p><ul><li>This job requires US citizenship. Are you a US citizen?</li><li>Do you have experience with spacecraft and space missions?</li></ul><p>Work Location: Hybrid remote in Littleton, CO 80127</p>

Orion Ground Data Systems Engineer

Whatnot

<div>
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  <strong>
   🚀 Join the Future of Commerce with Whatnot!
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  </strong>
 </strong>
 Whatnot is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops.
 <br/>
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 As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.
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 We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce.
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  💻 Role
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 At Whatnot data engineers build foundational data systems that power product development, experimentation, machine learning, and operational decision-making across the company. As an Data Engineer on the Notifications Platform, you will play a critical role in owning and evolving one of the highest-volume and highest-impact data domains at Whatnot.
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 Notifications generate hundreds of millions of events per day, and the underlying data systems support everything from ML iteration and experimentation to adhoc engineering debugging. In this role, you will define the technical direction for the Notifications data mart, harden it to production-grade reliability, and set new patterns for domain-owned data engineering.
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 Working in a highly cross-functional role, you will collaborate closely with Product Engineers, Data Scientists, ML Engineers, and the Analytics Platform team. You&rsquo;ll make key architectural decisions around data modeling, reliability, latency, and cost &mdash; and then make them real.
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  On Any Given Day, You Will
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   Own data architecture end-to-end. Define how we capture, model, and serve critical business data&mdash;then implement it in production. You&rsquo;ll make architectural decisions around storage formats, compute patterns, and SLAs that balance cost, scalability, and consistency.
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   Build mission-critical pipelines. Develop and operate batch data workflows that process high-volume events related to notifications with tight guarantees for latency, completeness, and accuracy.
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   Design and implement canonical models. Create domain-oriented data models that serve as the source of truth for analytics, ML, and production applications. Establish and enforce modeling standards, ownership boundaries, and data contracts across teams.
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   Enforce data quality at scale. Build tests, lineage, monitoring, and reconciliation systems that make every dataset observable and every anomaly actionable.
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   Automate operational workflows. Partner with business systems and platform teams to eliminate manual data handoffs and reconcile data across services, warehouses, and external systems.
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   Enable insights and experimentation. Support analytics, ML, and product engineering teams by exposing high-quality, self-healing, maintainable data assets.
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  </li>
 </ul>
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  We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs.
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 <strong>
  👋 You
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 </strong>
 Curious about who thrives at Whatnot? We&rsquo;ve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here.
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 As our next Data Engineer, you bring deep experience designing reliable, scalable data systems and are excited to take true ownership of a complex product domain.
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 You should have 5+ years of experience in the data or software engineering domain, plus:
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   Strong experience building and maintaining production-grade data pipelines with clear SLAs, monitoring, and alerting
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   Deep expertise in SQL, including complex model graphs, dependency management, and performance optimization
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  <li>
   Are comfortable writing production-grade code in Python or SQL languages, and integrating with CI/CD and infrastructure-as-code workflows.
  </li>
  <li>
   Have deep hands-on expertise with modern data tooling across ingestion (e.g., Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations).
  </li>
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   Have operated cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
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   Proven track record working with large-scale datasets (hundreds of millions of rows per day)
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   Experience designing data models that balance analytics, ML, and operational debugging use cases
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   Strong systems thinking &mdash; you consider correctness, latency, cost, and maintainability together
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   Self-starter ethic, thriving under a high level of autonomy
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   Exceptional interpersonal and communication skills in cross-functional environments
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  💰Compensation For Full-Time (Salary)
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  US based applicants:
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 $195,000/year to $230,000/year + benefits + equity.
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 The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.
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  🎁 Benefits
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   Generous Holiday and Time off Policy
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   Health Insurance options including Medical, Dental, Vision
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   Work From Home Support
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    Home office setup allowance
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    Monthly allowance for cell phone and internet
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   Care benefits
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    Monthly allowance for wellness
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    Annual allowance towards Childcare
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    Lifetime benefit for family planning, such as adoption or fertility expenses
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  </ul>
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   Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
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   Monthly allowance to dogfood the app
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   <li>
    All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).
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  </ul>
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   Parental Leave
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    16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.
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   💛 EOE
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 Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.
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 Compensation Range: $180K - $260K
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Data Engineer, Notifications

Keyrock

<div><h1 class="jobSectionHeader"><b>Senior Data Engineer</b></h1><p></p><h1 class="jobSectionHeader"><b>
About Keyrock</b></h1><p>
Since our beginnings in 2017, we've grown to be a leading change-maker in the digital asset space, renowned for our partnerships and innovation.</p><p>
Today, we partner with over 250 team members around the world. Our diverse team hails from 42 nationalities, with backgrounds ranging from self-taught DeFi natives to PhDs. Predominantly remote, we have hubs in London, Brussels, and Singapore, and host regular online and offline hangouts to keep the crew tight.</p><p>
We are trading on more than 80 trading venues, and working with a wide array of asset issuers. As a well-established market maker, our distinctive expertise led us to expand rapidly. Today, our services span market making, options trading, high-frequency trading, OTC, and DeFi trading desks.</p><p>
But we&rsquo;re more than a service provider. We&rsquo;re an initiator. We're pioneers in adopting the Rust Development language for our algorithmic trading, and champions of its use in the industry. We support the growth of Web3 startups through our Accelerator Program. We upgrade ecosystems by injecting liquidity into promising DeFi, RWA, and NFT protocols. And we push the industry's progress with our research and governance initiatives.</p><p>
At Keyrock, we're not just envisioning the future of digital assets. We're actively building it.</p><p></p><h2 class="jobSectionHeader"><b>
About the team and why the role exists</b></h2><p>
The Central Data Team (CDT) is only a few months old, but data has been Keyrock's lifeblood since day one. We're now building the Keyrock Data Platform to give Keyrockers, and the AI agents working alongside them, the data and context they need to act fast and autonomously within agreed boundaries and aligned with our shared goals. Doing that means taking data from across the company and making sense of it in real time for all the functions that depend on it: trading desks, wealth and asset management, product, risk, finance, compliance, and research to name a few.</p><p>
You'd be one of the early hires in CDT and we expect you to contribute to most of the bigger decisions and build work. The standards we settle on and the way the team ends up working are still open.</p><p></p><h2 class="jobSectionHeader"><b>
What You&rsquo;ll Do</b></h2><ul><li><p>
Build streaming and batch pipelines that ingest, normalise, and distribute market, trading, and portfolio data, resilient to feed and exchange failures.</p></li><li><p>
Build the self-serve tooling (SDKs, patterns, templates, AI agents) so other teams publish, consume, and build on data products without waiting on us.</p></li><li><p>
Own data contracts and schema evolution. Keep schema changes from turning into multi-team coordination events.</p></li><li><p>
Design the lakehouse and time-series layer around consumer query patterns.</p></li><li><p>
Build and evolve the Data Governance and Data Quality Framework: stale-feed detection, schema validation, range checks, idempotent writes, lineage, ownership, self-healing.</p></li><li><p>
Build the derived analytics the business runs on: cross-exchange spreads, VWAP at depth, order book microstructure for the desks; portfolio views, exposure, performance for wealth and asset management.</p></li><li><p>
Make observability, cost, and performance first-class from day one.</p></li><li><p>
Treat infrastructure as code (Docker, Terraform, CI/CD) alongside our Central Infrastructure Team.</p></li><li><p>
Work in the open: write things down, partner closely with Architecture, Infrastructure, Platform, and the rest of the teams.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
What We&rsquo;re Looking For</b></h2><p>
Tools matter less to us than how you think about problems. That said, here's the shape of the person we have in mind.</p><p>
Engineering Craft</p><ul><li><p>
8+ years of building production data systems that other people rely on.</p></li><li><p>
Strong proficiency in Python and SQL: not just being able to write a query, but being able to reason about what the engine is doing with it.</p></li><li><p>
Code that's easy for someone else to read, test, and delete later.</p></li><li><p>
Strong understanding of data modelling for both streaming and analytical workloads.</p></li><li><p>
Efficiency, quality, idempotency, and observability are taken seriously by default.</p></li></ul><p>
Systems Design</p><ul><li><p>
You've designed and operated streaming systems on Kafka, Redpanda, MSK, or Kinesis, and you have opinions about partitioning, consumer groups, offsets, and schema registries.</p></li><li><p>
You've used a time-series store in production (ClickHouse ideally; TimescaleDB, QuestDB, or similar are fine too) and can talk about table design as a function of query patterns.</p></li><li><p>
You've worked with a lakehouse architecture and reason about table layout, partitioning, and compaction as design choices that shape query performance and storage cost.</p></li><li><p>
You build for self-healing and idempotency. Reprocessing is safe, retries don't double-write, and the system recovers without a human in the loop.</p></li></ul><p>
Operational Readiness</p><ul><li><p>
Docker, Terraform, and CI/CD are how you work, not a separate &quot;DevOps&quot; thing.</p></li><li><p>
You think about cost and performance early.</p></li><li><p>
You instrument as you build: logs, metrics, and traces are part of the system from day one.</p></li><li><p>
You design for data quality and governance up front covering contracts, validation, lineage, and ownership</p></li></ul><p>
How You Think and Work</p><ul><li><p>
You reason from first principles when a problem is new, stay pragmatic when it isn't, and update your view when you learn more.</p></li><li><p>
You treat the trading desks, wealth and asset management, product, risk, finance, compliance, and research as customers of what you build, and communicate with them that way.</p></li><li><p>
You optimise for outcomes over output. A smaller, simpler thing that ships and works beats a bigger thing that doesn't.</p></li><li><p>
You take ownership end-to-end: design, ship, operate, improve.</p></li><li><p>
You say what you think including when it's an unpopular take. You change your mind when the argument is better.</p></li><li><p>
You make the people around you better. Reviews are real, juniors grow from working with you, and peers want to work with you again.</p></li><li><p>
You're curious about how markets work. Data engineering on its own won't keep you interested here.</p></li><li><p>
You're honest about what you know and what you don't, and quick to close the gap.</p></li><li><p>
You understand financial market data: order books, trades, reference data, portfolios, exposures. Crypto, TradFi, or both are a strong plus.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Nice to Have</b></h2><ul><li><p>
Lakehouse experience with Apache Iceberg or Delta Lake.</p></li><li><p>
Familiarity with DataHub or similar metadata/lineage platforms.</p></li><li><p>
Rust. Some of our performance-critical services are written in it. Interest is welcome; fluency isn't required.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
What You&rsquo;ll Get</b></h2><ul><li><p>
A from-scratch mandate. You'll be among the first hires in CDT, and the platform, the standards, and the team culture are yours to shape with us.</p></li><li><p>
Strong partners. Close working relationships with Architecture, Infrastructure, Platform, and the desks themselves. You won't be building data in a vacuum.</p></li><li><p>
Autonomy on how you work. Flexible hours, remote-first, business-hours on-call shared across the team.</p></li><li><p>
A competitive salary package, with various benefits.</p></li><li><p>
A team that likes each other. Regular online get-togethers and a yearly onsite where everyone's in the same room.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Our Recruitment Process</b></h2><p>
We&rsquo;re after those with the right skills and a conscious choice to join our field. The perfect fit? Someone who&rsquo;s driven, collaborative, acts with ownership and delivers solid, scalable outcomes. As an employer we are committed to building a positive and collaborative work environment. We welcome employees of all backgrounds, and hire, reward and promote entirely based on merit and performance. Due to the nature of our business and external requirements, we perform background checks on all potential employees, passing which is a prerequisite to join Key</p></div>

Senior Data Engineer

Tulsa Community Foundation

<div>
 <strong>
  Description
  <br/>
  <br/>
 </strong>
 <strong>
  ABOUT THE ORGANIZATION
  <br/>
  <br/>
 </strong>
 Tulsa For You and Me is a portfolio of talent and economic development programs working to strengthen Tulsa&rsquo;s long-term economic vitality, expand access to opportunity, and build a more vibrant and inclusive city. Operated under the stewardship of the George Kaiser Family Foundation&reg; (GKFF&reg;), affiliated programs include nationally recognized organizations such as Tulsa Remote, LLC, Tulsa Innovation Labs, LLC, Build In Tulsa, LLC, Experience Tulsa, Atlas School, LLC, Campus Tulsa program, Tulsa Service Year program, and others.
 <br/>
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 Integrated Strategies is Tulsa For You&rsquo;s centralized data, systems, and analytics team, helping programs operate more effectively, make better decisions, and scale with stronger internal infrastructure. The team&rsquo;s work spans Data &amp; Systems, CRM Platform Solutions, and Analytics&mdash;building the data environments, technical solutions, and analytical insight needed to support cross-program execution.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 In this position, you will serve as a key technical contributor within Tulsa For You&rsquo;s Data &amp; Systems environment, helping build and maintain the backend infrastructure that powers reporting, analytics, cross-system integrations, and reliable organizational data operations.
 <br/>
 <br/>
 This role requires strong hands-on experience in Python-based data engineering, cloud data environments, relational databases, and backend systems integration. You will support the full lifecycle of organizational data movement&mdash;from ingestion and transformation through warehouse optimization, monitoring, troubleshooting, and long-term systems improvement&mdash;ensuring analysts and program teams have reliable, well-structured, and trustworthy data to support decision-making.
 <br/>
 <br/>
 Success in this role requires high initiative, strong resourcefulness, and comfort operating in an environment where not every solution is predefined. The ideal candidate is someone who enjoys digging into unfamiliar technical problems, researching viable paths forward, and collaborating with others to build practical solutions in a dynamic setting.
 <br/>
 <br/>
 <strong>
  Essential Functions And Responsibilities
  <br/>
  <br/>
 </strong>
 <strong>
  Data Engineering &amp; Systems Management
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Build, maintain, and continuously improve scalable data pipelines, integrations, and warehouse workloads that support reliable and efficient data operations across the organization.
  </li>
  <li>
   Design and implement backend integrations for new and existing data sources&mdash;including APIs, databases, file-based feeds, cloud platforms, and third-party systems&mdash;to ensure accurate and dependable data movement.
  </li>
  <li>
   Develop, test, deploy, and support reusable data workflows, transformation jobs, warehouse objects, scripts, and related engineering components.
  </li>
  <li>
   Monitor pipeline, integration, and warehouse performance; proactively troubleshoot failures, optimize system reliability, and resolve data processing issues.
  </li>
  <li>
   Establish and maintain logging, alerting, automated monitoring, and data quality controls that strengthen visibility, issue detection, and long-term operational stability.
  </li>
  <li>
   Support secure data handling, system access controls, and governance practices to ensure organizational data is managed responsibly and in accordance with internal standards.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Systems Improvement &amp; Technical Collaboration
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strengthen backend data architecture, engineering standards, and technical workflows to improve maintainability, scalability, and delivery speed.
  </li>
  <li>
   Evaluate and apply modern tools, technologies, and engineering practices that improve the resilience and effectiveness of the overall data environment.
  </li>
  <li>
   Create and maintain technical documentation across pipelines, integrations, warehouse models, and backend workflows to support team continuity and long-term sustainability.
  </li>
  <li>
   Partner closely with analysts, technical teammates, vendors, and internal stakeholders to ensure backend data systems reliably support reporting, analytics, and operational decision-making.
  </li>
  <li>
   Other duties as assigned.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <strong>
  Education &amp; Experience:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   4+ years of professional experience in data engineering, cloud data infrastructure, backend integrations, or related technical roles supporting enterprise data environments.
  </li>
  <li>
   3+ years of hands-on experience developing and maintaining production-grade data pipelines, transformations, and backend workflows using Python.
  </li>
  <li>
   Demonstrated experience building or supporting API-based integrations and automated cloud data workflows across multiple systems.
  </li>
  <li>
   Experience working within version-controlled development environments and applying collaborative software engineering practices.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Skills &amp; Abilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strong capability designing and building reliable, scalable data pipelines and backend data workflows in cloud-based environments.
  </li>
  <li>
   Strong command of SQL, relational databases, and data modeling concepts, with the ability to structure and optimize data for downstream use.
  </li>
  <li>
   Proven ability to integrate and manage data across multiple systems, including APIs, databases, cloud services, and third-party platforms.
  </li>
  <li>
   Strong understanding of modern software engineering and deployment practices, including version control, testing, code review, and release workflows.
  </li>
  <li>
   Strong working knowledge of cloud environments and the core services that support data systems, including storage, compute, orchestration, monitoring, and security.
  </li>
  <li>
   Strong troubleshooting and problem-solving ability, with a focus on diagnosing failures, improving system reliability, and maintaining data integrity.
  </li>
  <li>
   Ability to operate effectively in evolving technical environments, bringing structure, sound judgment, and continuous improvement to systems and processes.
  </li>
  <li>
   Ability to work independently and collaboratively with technical teammates, vendors, analysts, and internal stakeholders.
  </li>
  <li>
   Strong written and verbal communication skills, including the ability to document systems clearly and explain technical concepts to technical and non-technical audiences.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience designing and supporting cloud-based data solutions within GCP and Azure strongly preferred
  </li>
  <li>
   Exposure to Infrastructure as Code (IaC), deployment automation, or related practices used to manage cloud-based technical environments..
  </li>
  <li>
   Experience working in Agile, sprint-based technical environments and using workflow management tools such as Jira and/or JSM.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Physical Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Position requires prolonged periods of sitting and working at a computer, including regular use of a keyboard and other standard office equipment.
  </li>
  <li>
   Position requires the ability to read, analyze, and visually review technical information and digital systems for extended periods of time.
  </li>
  <li>
   Position requires limited travel, predominantly for professional development and relevant organizational needs.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Hours &amp; Location:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   You must live in or be able to relocate to Tulsa, OK or the surrounding area.
  </li>
  <li>
   This is a hybrid position within an in-office leaning, highly collaborative work environment. Team members are generally expected to work onsite a minimum of three days per week, with additional hybrid flexibility available based on business needs, work demands, and supervisor approval.
  </li>
  <li>
   This is a full-time position with an expectation of working 40 hours per week.
  </li>
  <li>
   The typical hours of operation are Monday through Friday, 8:00 a.m. to 5:00 p.m. with flexibility required for various events, meetings, and relevant business needs.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 As part of our overall compensation package, we offer work/life flexibility, comprehensive health benefits, paid time off, and generous retirement contributions designed to support you and your family.
 <br/>
 <br/>
 <ul>
  <li>
   100% employer paid medical, dental, and long-term disability for full-time employees only. Option to add vision and dependents.
  </li>
  <li>
   401(k) employee and employer contributions.
  </li>
  <li>
   Paid time off to support you while you are out of the office.
  </li>
  <li>
   Paid holidays so our employees can spend time with those they care about.
  </li>
  <li>
   Employer-paid AD&amp;D life insurance, with employee option to add supplemental life insurance.
  </li>
 </ul>
</div>


Data Engineer

Research and Development Solutions

<div><div><div><div><b>Posted date</b></div> <div>23rd April, 2026</div> <div><b>Last date to apply</b></div> <div>23rd May, 2026</div>
</div><br>
<div><div><b>Country</b></div> <div>Pakistan</div> <div><b>Locations</b></div> <div>Islamabad</div>
</div><br>
<div><div><b>Category</b></div> <div>Data Science
</div></div><br>
<div><div><b>Type</b></div> <div>Full Time</div> <div><b>Position</b></div> <div>1</div>
</div><br>
<div><div><b>Experience</b></div> <div>3 years</div></div></div></div>
<br><p></p><div><p>Terms of Reference (TOR)</p>
<p>Unit: Urban Impact Lab<br>
Reports to: Team Lead, Urban Impact Lab</p>
<p>About the role</p>
<p>
This is a core data role inside the Data Analytics and Systems vertical, Urban Imoact Lab (UIL). The incumbent owns RADS's data infrastructure end to end. That includes designing and maintaining data collection systems, building and running pipelines between survey servers and program databases, managing the database and BI layer behind AapiVerse, developing dashboards across different tools and environments, and automating the recurring extraction, cleaning, and reporting work that keeps field operations and program monitoring functional. The role is hands-on and engineering-first. Research and policy outputs are handled by other verticals; this role exists to make their work possible.</p>
<p>
Key responsibilities</p>
<p><b>
Data collection systems (SurveyCTO)</b></p>
<ul>
<li>Own RADS's SurveyCTO environment: form design, complex skip logic, relevance and constraint rules, encrypted case management, enumerator assignment, review workflows, server administration, and user roles.</li>
<li>Localize and version instruments between English and Urdu, and maintain an internal library of reusable form components.</li>
<li>Build high-frequency checks, back-check workflows, and enumerator performance dashboards that catch data issues within 24 to 48 hours of collection.</li>
</ul>
<p><b>Data pipelines and ETL</b></p>
<ul>
<li>Design, build, and maintain production-grade pipelines that move data from SurveyCTO, the MySQL platform, and external administrative sources into a clean, documented, analysis-ready warehouse.</li>
<li>Write clean, version-controlled ETL code in Python (pandas, SQLAlchemy) and Stata; schedule recurring jobs and monitor them.</li>
<li>Maintain raw, intermediate, and output data layers with full lineage documentation, codebooks, and data dictionaries for every dataset produced.</li>
</ul>
<p><b>Database and BI layer</b></p>
<ul>
<li>Manage RADS's MySQL database and its schema&rsquo;s, and extend the schema as new modules and studies come online.</li>
<li>Resolve schema issues, relationship conflicts, and performance bottlenecks in coordination with the software team.</li>
</ul>
<p><b>Dashboard development across tools and environments</b></p>
<ul>
<li>Build and maintain production dashboards for program management, field operations, donor reporting, and internal analytics, choosing the right tool for the audience and use case.</li>
<li>Work across a mix of BI platforms (Power BI, Tableau, Metabase or Superset) and code-based environments (Python with Streamlit or Dash, R with Shiny, and web-based visualizations with Leaflet or Plotly).</li>
<li>Own the refresh schedule, access controls, and version history for every dashboard in production.</li>
<li>Embed dashboards into the AapiVerse platform and donor-facing microsites where needed.</li>
<li>Retire dashboards that are no longer used and document what replaced them, so the surface area stays manageable.</li>
</ul>
<p><b>Automation and integration</b></p>
<ul>
<li>Automate recurring data extraction, cleaning, and reporting tasks.</li>
<li>Build browser-based automation (Playwright) where public or partner data is only accessible through a UI.</li>
<li>Integrate geospatial layers such as catchment polygons, facility locations, and household GPS using GeoPandas and QGIS, and publish web maps where useful.</li>
</ul>
<p><b>Data governance</b></p>
<ul>
<li>Maintain IRB compliance, PII handling standards, encryption at rest, access controls, and retention policies across all RADS data assets.</li>
<li>Keep the data inventory, ROPA, and consent artifact records up to date.</li>
</ul>
<p><b>Team coordination</b></p>
<ul>
<li>Supervise data officers, junior analysts, and short-term consultants on the vertical's workstreams.</li>
<li>Coordinate with the MeriSehat/AapiVerse software team on platform data structures, UAT cycles, and release planning.</li>
<li>Act as the data point of contact for other RADS verticals including research, program, and partnerships, ensuring their data needs are served reliably.</li>
</ul><p>Qualifications</p>
<p>Required</p>
<ul><li>Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Economics, Public Health, or a related quantitative field.</li>
<li>3 to 4 years of hands-on experience in data systems, pipelines, and analytics, ideally in a research, health, or development setting.</li>
<li><b>SurveyCTO: </b>demonstrated experience designing complex forms, managing the server, and running review and back-check workflows.</li>
<li><b>Python: </b>strong working proficiency in pandas, numpy, and SQLAlchemy; comfort writing unattended scripts and small automations.</li>
<li><b>Stata: </b>fluency for data cleaning, reshaping, and merging large survey datasets.</li>
<li><b>SQL and MySQL: </b>able to write non-trivial queries, design schemas, and debug relational models.</li>
<li><b>Dashboarding: </b>production experience with at least one BI tool (Power BI, Tableau, Metabase, or Superset) and at least one code-based framework (Streamlit, Dash, Shiny, or equivalent).</li>
</ul><p>Preferred</p>
<ul><li>Experience embedding dashboards into web applications and working with front-end teams on integration.</li>
<li>Experience with geospatial stacks (GeoPandas, QGIS, Leaflet) and browser automation (Playwright, Selenium).</li>
<li>Familiarity with cloud environments (AWS or GCP) and workflow orchestration tools.</li>
<li>Exposure to NIH and FCDO data management and sharing requirements.</li>
<li>Experience building data systems for RCTs or longitudinal household studies.</li>
</ul><p>Skills and attributes</p>
<p>
Engineering discipline, with documentation, reproducibility, and version control as defaults. Comfort moving between a SurveyCTO form, a Python script, a MySQL schema, and a dashboard in the same day. Good judgment about which dashboarding tool fits which audience, rather than defaulting to one. Ability to own multiple concurrent systems without close supervision. Collaborative temperament when working across software, field, and program teams. A preference for durable infrastructure over one-off fixes.</p>
<p>
How to apply</p>
<div><ul><li>Curriculum vitae.</li></ul>
<ul><li>A brief cover letter (one page).</li></ul>
<ul><li>A technical artifact of your choice, such as a GitHub repository, a SurveyCTO form export, a dashboard link or file (Power BI, Tableau, Streamlit, or similar), a Stata project, or a data pipeline, that demonstrates your systems work.</li></ul></div></div><p></p>

Senior Associate (Data Analytics and Systems)

Michigan Farm Bureau

<div>OBJECTIVE:
<div><b>
Data Engineer Objective</b></div><div>
To build, manage, optimize, and assist in the design of data pipelines in support of information, analytics, and strategic business needs across the enterprise.</div>
RESPONSIBILITIES:
<div><b>
Data Engineer Responsibilities</b></div><div>
Identify and understand source data systems and data flow between systems. Recognize changes in those systems and assess impacts on data pipelines. Adapt data pipelines to accommodate modifications triggered by source system changes or business requirements.</div><div></div><div><br>
Work closely with other IT or business personas while participating on projects. Demonstrate proficiency in understanding requirements and assist the team by offering expertise on data-related technical issues. Provide continuous updates on progress to project stakeholders, as well as issues or dependencies that put milestones at risk. Communicate efficiently, both written and verbally. Ask clarifying questions when needed and demonstrate teamwork and collaboration with the project team to ensure deliverables meet expectations.</div><div></div><div><br>
Assemble large sets of data that meet non-functional and functional business requirements and that comply to best practices and guidelines set by architects, senior and lead engineers.</div>
QUALIFICATIONS:
<div><b>
Data Engineer Qualifications</b></div><div><b>
Required
</b></div><div>Bachelor&rsquo;s degree in information systems, computer science, or related field required, or equivalent experience may be considered.</div><div></div><div><br>
Three to five years&rsquo; experience working with Microsoft SQL Server, T-SQL, Visual Studio IDE, and SSIS (or equivalent ETL platforms) required.</div><div></div><div><br>
Current knowledge of computer hardware, operating systems, program language(s) and tools, testing techniques and tools, program specification and interpretation required.</div><div></div><div><br>
Working knowledge of systems design and analysis tools and techniques required.</div><div></div><div><br>
Willingness to pursue continuing job-related training and education in systems and insurance required.</div><div></div><div><b><br>
Preferred</b></div><div>
Working knowledge of transactional, analytical, big data structures preferred.</div><div></div><div><br>
Understanding database best practices and technologies such as types of compression, indexes, security, data types, and AlwaysOn preferred.</div><div></div><div><br>
Prior experience at an insurance company or on projects for an insurance company preferred.</div><p>
Microsoft Fabric experience preferred.<br>
<br>
<b>Note:</b> This is a Hybrid position working remotely (from the state of Michigan) and from the Farm Bureau Home Office located in Lansing, Michigan.<br>
<br>
If a candidate is not selected, a Senior Data Engineer may be considered on the level of experience and qualifications.<br>
<br>
Farm Bureau offers a full benefit package including medical, dental, vision, and 401K.</p><div>
PM19</div></div>

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