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KNOWFINITY

<div>
 We are hiring a
 
 Data Engineer
 
 on behalf of one of our prestigious
 
 Fortune 500 Healthcare clients in the United States
 
 . This is an excellent opportunity to work on large-scale healthcare data platforms, modern cloud technologies, and enterprise-grade data engineering initiatives that directly support critical business and patient-care operations.
 
 
 The ideal candidate should have hands-on experience in building scalable data pipelines, working with cloud-based data ecosystems, and supporting analytics and reporting solutions in a fast-paced enterprise environment.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
 </li>
 <li>
 Build and optimize data workflows using modern cloud and big data technologies.
 </li>
 <li>
 Collaborate with data analysts, business stakeholders, and engineering teams to deliver reliable data solutions.
 </li>
 <li>
 Develop data integration processes across multiple healthcare and enterprise systems.
 </li>
 <li>
 Ensure data quality, integrity, governance, and security standards are maintained.
 </li>
 <li>
 Monitor and troubleshoot data pipelines and production jobs.
 </li>
 <li>
 Support reporting, analytics, and business intelligence initiatives.
 </li>
 <li>
 Participate in performance tuning and optimization of databases and data processing systems.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 2+ years of experience as a Data Engineer or in a related data-focused role.
 </li>
 <li>
 Strong experience with SQL and relational databases.
 </li>
 <li>
 Hands-on experience with Python, PySpark, or Scala.
 </li>
 <li>
 Experience working with ETL tools and data pipeline development.
 </li>
 <li>
 Familiarity with cloud platforms such as AWS, Azure, or GCP.
 </li>
 <li>
 Experience with big data technologies like Spark, Hadoop, or Databricks is preferred.
 </li>
 <li>
 Knowledge of data warehousing concepts and dimensional modeling.
 </li>
 <li>
 Strong analytical, problem-solving, and communication skills.
 </li>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Information Technology, Engineering, or related field.
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Healthcare domain experience preferred
 </li>
 <li>
 Exposure to HIPAA-compliant environments is an advantage
 </li>
 <li>
 Strong analytical and problem-solving skills
 
 
 </li>
 </ul>
 
 What We Offer
 
 
 
 <ul>
 <li>
 Opportunity to work with a Fortune 500 Healthcare organization.
 </li>
 <li>
 Exposure to enterprise-scale cloud and data engineering projects.
 </li>
 <li>
 Collaborative and technology-driven work environment.
 </li>
 <li>
 Competitive compensation package.
 </li>
 <li>
 Long-term growth and career advancement opportunities.
 
 
 </li>
 </ul>
 
 Work Authorization
 
 
 
 Candidates must be legally authorized to work in the United States. Visa sponsorship is available for eligible candidates.
 
 
 Skills: data engineering,python,big data,azure,aws,sql,gcp,cloud,analytics,healthcare,data,etl
</div>

Data Engineer

The Cypress Group

<div>
 
 Our client is an industry leader in multi-screen audience ad-serving reaching over 100 million households. They are currently expanding their Data Engineering team based in New York City, NY. This role is hybrid on-site in the NYC Headquarters.
 
 
 
 
 
 Qualified candidates will have 3+ years of professional hands-on experience working as a Data Engineer including hands-on experience with a combination of the following: Python, Scala, Spark or PySpark, AWS, ETL, SQL. The Data Engineer will build data pipelines and analytics tools by writing and maintining a reliable, scalable code base. Experience with columnar data stores (Parquet, Snowflake, etc.) is a plus. BSCS or equivalent is preferred.
 
 
 
 
 
 This role features competitive base salary and performance-based bonus, comprehensive health benefits, 401(k) with company matching and other perks. Please send your resume to nyjobs@cypressg.com for immediate consideration.
 
</div>

Kforce Inc

<div>
 
 Responsibilities
 
 
 
 Kforce's client, a leading global investment firm is seeking a Data Engineer, Infrastructure to join its core engineering team in Boston, MA. Summary: This is a high-impact technical leadership role focused on building elite data infrastructure to power advanced AI and investment platforms. You will design world-class pipelines that process massive financial datasets, integrate AI-driven document extraction, and bridge diverse cloud-native databases. In this role, you will define the blueprint for how the firm structures and leverages data, ensuring high performance, integrity, and accessibility for mission-critical services. Key Responsibilities:
 
 
 <ul>
 <li>
 Architect and modernize a unified data fabric, setting standards for data access, governance, and productization across the enterprise; Lead the evolution of an Iceberg-based lakehouse, overseeing ingestion, streaming, replication, and lifecycle management
 </li>
 <li>
 Define the compute architecture across stateful and distributed layers, balancing scalability with cost efficiency
 </li>
 <li>
 Implement event-driven patterns to ensure low-latency, observable data flows for real-time system integration
 </li>
 <li>
 Expand platform capabilities to support AI/ML, including feature-ready pipelines and scalable services for model training and inference
 </li>
 <li>
 Convert business priorities into a technical roadmap, making critical architecture decisions that maximize long-term platform value
 </li>
 <li>
 Partner with application teams and stakeholders to serve as the lead authority for strategic data domains
 </li>
 <li>
 Enforce high engineering standards for data quality, lineage, security, and operational excellence
 </li>
 <li>
 Mentor junior talent, fostering a culture of design rigor and implementation quality
 </li>
 <li>
 Conduct R&amp;D on emerging technologies to recommend production-ready solutions for the firm's target architecture
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Degree in Computer Science, Engineering, or a related field; Advanced degree preferred
 </li>
 <li>
 4+ years in data or platform engineering, with a track record of senior-level technical leadership
 </li>
 <li>
 A "platform-first" mindset with experience delivering enterprise-scale lakehouse ecosystems
 </li>
 <li>
 Deep expertise in Apache Iceberg and open table formats, including partitioning and performance tuning
 </li>
 <li>
 Strong grasp of distributed compute models, workload orchestration, and fault-tolerant system design
 </li>
 <li>
 Proven success implementing streaming architectures and modern messaging patterns
 </li>
 <li>
 Experience building data services that support AI/ML workflows and production model deployments
 </li>
 <li>
 Advanced proficiency in Python and SQL; Java or Scala skills are a major plus
 </li>
 <li>
 Familiarity with cloud-native/containerized environments and infrastructure automation
 </li>
 <li>
 Excellent communication skills with the ability to influence technical and non-technical stakeholders
 </li>
 <li>
 Exposure to large-scale AI orchestration frameworks is highly desirable
 
 
 </li>
 </ul>
 The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
 
 
 We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability &amp; ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
 
 
 Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
 
 
 This job is not eligible for bonuses, incentives or commissions.
 
 
 Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
 
 
 By clicking &ldquo;Apply Today&rdquo; you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.
</div>

Data Engineer- Infrastructure

Capgemini

<div><div><div><div>Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you&rsquo;d like, where you&rsquo;ll be supported and inspired by a collaborative community of colleagues around the world, and where you&rsquo;ll be able to reimagine what&rsquo;s possible. Join us and help the world&rsquo;s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
<div><div><div><h2 class="jobSectionHeader">Onsite location : New York, Chicago &amp; Atlanta</h2>
</div></div><div></div><div><div><h2 class="jobSectionHeader">Job Description</h2> 
</div><div> 
Seeking a highly skilled and motivated Senior Data Engineer to support enterprise data modernization initiatives.
This role requires deep expertise in Python, AWS, and relational databases, combined with strong experience in mainframe technologies (VSAM, DB2).
 
The candidate will play a critical role in end-to-end data migration, transforming legacy data systems into modern, scalable cloud-based architectures while ensuring data accuracy, integrity, and governance standards.
 
 
Key Responsibilities:
 
Lead and execute end-to-end data migration efforts, including planning, design, execution, validation, and post-migration support.
 
Analyze legacy data structures (VSAM, DB2) and design transformation strategies into modern RDBMS and AWS environments.
 
Develop and maintain data pipelines and automation scripts using Python.
 
Design, implement, and maintain data models (conceptual, logical, and physical).
 
Manage and administer AWS RDS environments, ensuring high availability, performance optimization, and security compliance.
 
Collaborate with business and technology stakeholders to gather and translate requirements into scalable data solutions.
 
Ensure adherence to data governance, data quality, and compliance standards.
 
Troubleshoot data-related issues and provide timely resolution.
 
Prepare technical documentation for data models, migration workflows, and architecture designs.
</div></div></div>The base compensation range for this role in the posted location is: $86129 to $127189
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. 
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
<ul><li>Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave</li>
</ul><ul><li>Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)</li>
<li>Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)</li>
<li>Life and disability insurance</li>
<li>Employee assistance programs</li>
<li>Other benefits as provided by local policy and eligibility</li>
</ul>Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini&rsquo;s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. 
Disclaimers
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.
Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law 
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.</div></div></div></div>

Python & AWS Data Engineer

Cohere

<div>
 
 Who are we?
 
 
 
 Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
 
 
 We&rsquo;re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
 
 
 We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
 
 
 We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us!
 
 
 
 Why this role?
 
 
 
 We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a member of our Analytics &amp; Data Insights team, you'll tackle the kind of problems that don't have textbook answers yet, launch products that didn't exist a year ago, and help enterprises understand what foundational AI actually means for their bottom line.
 
 
 
 As a Data Engineer, You Will
 
 
 
 <ul>
 <li>
 Work directly on new customer experiences built on one of the most advanced AI systems in the world
 </li>
 <li>
 Collaborate daily with researchers and engineers who are some of the best in the world at what they do
 </li>
 <li>
 Run implementations end-to-end and see initiatives through to real outcomes
 </li>
 <li>
 Partner across research, marketing, sales, and finance to help define how Cohere grows, with your recommendations feeding directly into products and strategy
 
 
 </li>
 </ul>
 
 You May Be a Good Fit If You Have
 
 
 
 <ul>
 <li>
 5+ years of experience working on production-grade data processing systems
 </li>
 <li>
 Strong command of Python and SQL
 </li>
 <li>
 Experience with distributed data processing frameworks such as Apache Beam, Spark, or Flink, alongside large-scale data system design
 </li>
 <li>
 The ability to transform unstructured data into performant datasets in relational databases and blob storage
 </li>
 <li>
 Familiarity with modern analytics stack tooling such as BigQuery, Airflow, or dbt
 </li>
 <li>
 Knowledge of Java or Golang (nice to have)
 </li>
 <li>
 Experience with Kubernetes (nice to have)
 </li>
 <li>
 Genuine excitement about AI - you follow the research, have opinions, and enjoy being in the weeds
 </li>
 <li>
 Comfort operating at the edge of what's known, with a desire to build something genuinely new rather than optimise what already exists
 
 
 </li>
 </ul>
 
 Full-Time Employees At Cohere Enjoy These Perks
 
 
 
 <ul>
 <li>
 A weekly lunch stipend of $75/&pound;75 or equivalent in your local currency for lunch.
 </li>
 <li>
 Full health and dental benefits, including a separate budget for mental health.
 </li>
 <li>
 RRSP matching, 401K, Pension Scheme.
 </li>
 <li>
 100% Parental Leave top-up for up to 6 months, for either parent.
 </li>
 <li>
 Annual enrichment benefits:
 
 
 </li>
 </ul>
 Arts &amp; culture, fitness/wellness, quality time, and a workspace improvement credit.
 
 
 Education &amp; learning stipend for conferences, courses, and coaching.
 
 
 <ul>
 <li>
 6 weeks of paid vacation (30 working days!)
 </li>
 <li>
 Budget for traveling to other offices if you are remote, plus an annual company offsite.
 
 
 </li>
 </ul>
 
 How And Where We Work
 
 
 
 <ul>
 <li>
 Cohere is remote-friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming soon.
 </li>
 <li>
 For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
 </li>
 <li>
 For those not near an office: a co-working benefit so you can work alongside others in your city.
 </li>
 <li>
 Everyone receives a $500 home office stipend to set up your workspace properly.
 
 
 </li>
 </ul>
 If any of the above doesn&rsquo;t line up exactly with your experience, we still encourage you to apply.
 
 
 We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.
 
 
 We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
</div>

Data Engineer, Data Foundations

Netbuilder

Location: New York (office-based) with travel to client sites as requiredSalary: Up to $140,000 per year (dependent on experience)Role type: Full-time, permanentDepartment: Technology Consulting &ndash; Observability PracticeNETbuilder is building an Observability Practice, and this is a senior delivery hire into it. You will join as a senior data pipeline engineer, working hands-on inside enterprise client teams to architect, deploy and operate the observability platforms and telemetry pipelines that sit at the heart of modern observability.This is primarily a hands-on delivery role &ndash; a senior individual-contributor position rather than a line-management one. Your focus is engineering across two fronts: designing and deploying the observability platforms themselves, and building the data pipelines that collect, route, transform, enrich and deliver telemetry reliably and cost-effectively across complex enterprise environments. You will be the senior technical authority on observability platform architecture and data pipelines for the engagements you work on. While there is no permanent team to manage, on specific engagements you will provide technical leadership &ndash; mentoring junior engineers, planning the workstream and allocating tasks across the delivery team.Consulting experience is preferred but not essential &ndash; what matters most is deep, current, hands-on expertise with industry-standard observability platforms and their pipeline and transformation tooling. If you would rather solve hard data-engineering and platform problems and lead through expertise than carry permanent people-management responsibility, this is the role.Key Responsibilities:Pipeline Engineering &amp; Delivery<ul><li>Design, build and operate telemetry pipelines that collect, route, transform, enrich, reduce and mask logs, metrics and traces at enterprise scale</li><li>Develop and maintain data transformation logic &ndash; parsing, restructuring, filtering and normalising telemetry across formats and schemas</li><li>Optimise pipelines for data quality, cost control and performance &ndash; reducing noise and volume without losing signal</li><li>Onboard complex applications and data sources onto observability platforms</li><li>Build, test and document reusable pipeline configurations, processors and templates</li><li>Monitor pipeline health and throughput, and troubleshoot ingestion, routing and delivery issues</li></ul>Platform Architecture &amp; Deployment<ul><li>Architect observability platform deployments &ndash; topology, sizing, high availability, resilience and scaling &ndash; to meet enterprise client requirements</li><li>Deploy, configure and operate observability platforms and their collection/agent fleets across cloud, hybrid and on-premises environments</li><li>Define deployment patterns and infrastructure-as-code for repeatable, automated platform rollouts</li><li>Integrate observability platforms with client infrastructure, data sources and downstream destinations</li><li>Own platform health, upgrades and capacity planning, and keep architecture and deployment documentation current</li></ul>Client Delivery<ul><li>Deliver observability platform and pipeline engagements directly with enterprise clients as a senior practitioner</li><li>Own delivery outcomes for the platform and pipeline workstreams on assigned engagements</li><li>Act as senior technical authority and escalation point for platform architecture, deployment and data pipeline issues</li><li>Lead troubleshooting and root-cause analysis across enterprise observability platforms and telemetry pipelines</li><li>Support pre-sales with technical scoping and solution design for platform and pipeline work</li><li>Translate client requirements into platform and pipeline designs that balance coverage, cost and compliance</li></ul>Engagement Leadership &amp; MentoringThis is engagement-scoped technical leadership rather than permanent line management &ndash; on specific engagements you will:<ul><li>Provide technical leadership as the senior practitioner, setting direction and quality standards for the platform and pipeline workstream</li><li>Plan the workstream &ndash; scope the work, sequence the tasks and allocate them across the engagement delivery team where required</li><li>Mentor and coach junior engineers and consultants working alongside you, sharing platform and pipeline expertise on the job</li><li>Co-ordinate with the wider engagement team and report progress on the workstream</li></ul>Tooling &amp; Practice Contribution<ul><li>Work hands-on across the observability tool landscape (see preferred tools below), applying each platform's architecture, deployment and data-pipelining capabilities</li><li>Stay current with platform capabilities, roadmaps and certifications</li><li>Contribute to NETbuilder's platform and pipeline methodology, toolkits and reusable assets</li></ul>Qualifications and Experience:<ul><li>Senior data pipeline engineering experience: demonstrable hands-on track record designing, building and operating telemetry/observability data pipelines at enterprise scale</li><li>Platform architecture and deployment experience: hands-on experience designing, deploying and operating observability platforms (topology, sizing, high availability and scaling) across cloud, hybrid and on-premises environments</li><li>Data transformation expertise: strong practical experience with parsing, routing, filtering, enrichment and normalisation of log, metric and trace data</li><li>Tooling experience: hands-on experience with the architecture, deployment and data-pipelining functionality of one or more industry-standard observability platforms (see preferred tools below)</li><li>Engagement leadership: comfortable mentoring junior engineers and planning and allocating tasks within a delivery team on an engagement, without formal line-management authority</li><li>Consulting experience: preferred but not essential &ndash; comfortable working directly within enterprise client teams</li></ul>Preferred Tool Experience:Hands-on experience with the architecture, deployment and data-pipelining functionality of one or more of the following platforms, in order of preference:<ul><li>Bindplane (ObservIQ / Google)</li><li>Dynatrace (OpenPipeline)</li><li>OpenTelemetry (Collector &ndash; receivers, processors and exporters)</li><li>Cribl (Stream)</li><li>Elastic (ingestpipelines)</li><li>Splunk</li></ul>Preferred Certifications:Certification in one or more of the following is preferred:<ul><li>Dynatrace Professional (Dynatrace Master advantageous)</li><li>OpenTelemetry Certified Associate (OTCA) &ndash; also covers Bindplane, which is OpenTelemetry-native</li><li>Cribl Certified Engineer (CC Engineer) or Cribl Certified Observability Engineer &ndash; Admin (CCOE Admin)</li><li>Elastic Certified Engineer</li><li>Splunk Enterprise Certified Architect</li></ul>Key Skills:<ul><li>Platform architecture and deployment: designing observability platform topology (sizing, HA, scaling) and deploying/automating platform and pipeline infrastructure as code</li><li>Pipeline and transformation tooling: deep expertise in one or more observability platforms and their transformation languages and processors</li><li>OpenTelemetry: strong working knowledge of the OpenTelemetry Collector (receivers, processors, exporters) and OTLP</li><li>Scripting and automation: Python, Bash</li><li>Data formats and parsing: JSON, regex, syslog, and common log, metric and trace formats</li><li>Cloud platform knowledge: AWS, Azure, and/or GCP</li><li>Container and orchestration: Kubernetes, Docker, OpenShift</li><li>Familiar with delivery and project tooling: JIRA, Confluence, ServiceNow</li></ul>About You:<ul><li>A hands-on engineer who would rather architect and build a solution than sit in a management meeting</li><li>Happy to lead through expertise &ndash; mentoring others, planning a workstream and giving direction on an engagement, even without a formal management title</li><li>Comfortable working directly inside enterprise client teams and engaging senior stakeholders</li><li>Rigorous about data quality, cost and reliability &ndash; you care about getting the right signal at the right price</li><li>Self-managing, delivery-focused and comfortable in a fast-moving environment</li><li>Naturally curious &ndash; you keep pace with a fast-evolving observability tooling landscape</li></ul>About NETbuilder:NETbuilder is a leading provider of digital solutions, software, consulting and managed services. We work across multiple sectors with specialist expertise in financial services, government, and commercial markets. Since 1999 we have been providing end-to-end solutions across Digital Delivery, Development and Technology. At our core we are a Digital Transformation consultancy with capabilities for onsite, onshore and offshore delivery.You will join a world-class team of experienced consultants, helping to build a new observability practice within the NETbuilder group.Why NETbuilder:<ul><li>Join a new observability practice as a senior technical specialist, working with cutting-edge observability platforms</li><li>Work with enterprise clients across multiple sectors</li><li>Competitive base salary: $120,000 - $140,000 (dependent on experience)</li><li>Continuous investment in professional development and certification</li><li>High-performance, close-knit team culture where individual contribution is recognised</li><li>Office-based New York, with travel to enterprise client sites</li></ul>Pay: Up to $140,000.00 per yearBenefits:<ul><li>Health insurance</li><li>Paid time off</li></ul>Application Question(s):<ul><li>Do you have a demonstrable hands-on track record of designing, building and operating telemetry/observability data pipelines?</li></ul>Ability to Commute:<ul><li>New York, NY 10036 (Required)</li></ul>Willingness to travel:<ul><li>25% (Required)</li></ul>Work Location: In person

Senior Data Pipeline Engineer

Kairon Health

<div><h1 class="jobSectionHeader">About Kairon Health</h1>
Kairon is the execution layer for healthcare. We turn fragmented claims and clinical data into actionable workflows that help ACOs and health networks actually capture their shared savings &mdash; not just measure them after the fact.
We&rsquo;re a seed-stage team of &lt;10, working with real customers managing real patient populations. Our platform spans practice intelligence, care operations, patient activation, and performance analytics. We&rsquo;re AI-native &mdash; not as a buzzword, but because our team builds with Claude, automated transcription, and intelligent workflows as core infrastructure, not bolt-on features.
We&rsquo;re at the stage where our early customers love the product and we need to make onboarding, support, and ongoing operations repeatable without losing the high-touch quality that got us here.<h1 class="jobSectionHeader">
Position Overview</h1>
We&rsquo;re seeking a Senior Product Engineer, Data Applications to own the product layer where data meets decision-making. You&rsquo;ll build the data-powered applications that surface intelligence directly to users &mdash; from the Performance App and ACO-in-a-Box tooling to interactive reporting, scorecards, and next-generation analytics experiences.
This is a full-stack, product-oriented engineering role. You&rsquo;ll design and implement end-to-end solutions (data models, APIs, and UI components) that bring Kairon&rsquo;s insights to life for practice leaders. You&rsquo;ll work closely with engineering leadership, product, and analytics teams to transform complex healthcare data into intuitive, high-impact tools.
You&rsquo;ll thrive here if you&rsquo;re as excited about what you build as why you&rsquo;re building it: an engineer who understands product trade-offs, can shape features from user requirements, and enjoys turning messy data into meaningful, elegant applications.<h1 class="jobSectionHeader">
Key Responsibilities</h1><ul><li>
Own the data-to-application layer: Design, build, and maintain data-driven applications such as performance dashboards, scorecards, and analytic workbenches.</li><li>
Architect end-to-end features: Connect backend models, APIs, and frontend components to deliver interactive insights within the Kairon platform.</li><li>
Collaborate with product and analytics: Translate user needs and clinical/financial metrics into intuitive visualizations and actionable interfaces.</li><li>
Advance in-app intelligence: Integrate data pipelines, LLM insights, and healthcare analytics into user-facing modules (Performance App, ACO-in-a-Box, CRM, and others).</li><li>
Uphold scalability and quality: Design for maintainability, reusability, and performance; implement tests and observability to ensure reliability.</li><li>
Contribute to design &amp; UX: Work with designers to create cohesive, user-friendly experiences that communicate complex data clearly.</li><li>
Champion engineering excellence: Establish best practices, documentation, and component libraries for future applications.</li><li>
Leverage modern AI-assisted tooling: Use LLMs to accelerate development, code review, and refactoring while maintaining rigorous standards.</li></ul><h1 class="jobSectionHeader">
Qualifications</h1><ul><li>
6+ years of professional experience building production web applications (frontend + backend).</li><li>
Strong proficiency in Python, Django/DRF, Vue, and SQL; experience with data visualization frameworks and API design.</li><li>
Experience designing or consuming data models and ETL pipelines (e.g., Snowflake, dbt, or similar).</li><li>
Proven ability to translate product requirements into technical architecture and deliver polished, high-impact user experiences.</li><li>
Familiarity with healthcare, analytics, or enterprise SaaS environments.</li><li>
Clear communication and cross-functional collaboration skills; comfort working directly with product and leadership.</li></ul><h1 class="jobSectionHeader">
Preferred Qualifications</h1><ul><li>
Experience in healthcare or value-based care analytics, EHR data, or claims data models.</li><li>
Prior work integrating LLM-driven insights, AI-based summarization, or contextual intelligence into applications.</li><li>
Strong understanding of data visualization principles and UX for analytics products.</li><li>
Background that spans both engineering and product management (technical PM, full-stack data apps, or similar hybrid roles).</li><li>
Previous experience in an early-stage or high-growth startup environment.</li></ul><h1 class="jobSectionHeader">
Why This Role</h1><ul><li>
Impact. You&rsquo;re not maintaining someone else&rsquo;s machine. You&rsquo;re building customer operations from the ground up at a company where the work directly affects whether patients get better care.</li><li>
Growth. This role has a clear trajectory. Depending on your strengths and interests, this becomes Head of Customer Success, Director of Implementations, or a Product leadership role as we scale. You&rsquo;ll have the context and relationships to grow into whatever the company needs most.</li><li>
Stage. We&rsquo;re past the &ldquo;will this work?&rdquo; phase &mdash; customers are live and getting value. We&rsquo;re in the &ldquo;how do we do this 10x without breaking?&rdquo; phase. That&rsquo;s the most interesting operational puzzle in a startup.</li><li>
Equity. You&rsquo;ll have meaningful ownership as one of our first 10 hires, with a real seat at the table.</li></ul>
Diversity and inclusion are core to our culture. If you are a member of an underrepresented group in tech, we strongly encourage you to apply.
Compensation Range: $170K - $190K</div>

Product Engineer, Data

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