analytics data engineer

Anthropic

<div>
 <strong>
  About Anthropic
  <br/>
  <br/>
 </strong>
 Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 As an Analytics Engineer, you will be an early member of the Data Science &amp; Analytics team building the foundation to scale analytics across our organization. You will collaborate with key stakeholders in Engineering, Product, GTM and other areas to build scalable solutions to transform data into key metrics reporting and insights. You will be responsible for ensuring teams have access to reliable, accurate metrics that can scale with our company&rsquo;s growth. You will also lead your own projects to enable self-serve insights to help teams make data-driven decisions.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Understand the data needs of stakeholder teams in terms of key data models and reporting, and translate that into technical requirements
  </li>
  <li>
   Define, build and manage key data pipelines in dbt that transform raw logs into canonical datasets
  </li>
  <li>
   Establish high data integrity standards and SLAs to ensure timely, accurate delivery of data
  </li>
  <li>
   Develop insightful and reliable dashboards to track performance of core metrics that will deliver insights to the whole company
  </li>
  <li>
   Build foundational data products, dashboards and tools to enable self-serve analytics to scale across the company
  </li>
  <li>
   Influence the future roadmap of Product and GTM teams from a data systems perspective
  </li>
  <li>
   Become an expert in our organization&rsquo;s data models and the company's data architecture
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  You Might Be a Good Fit If You Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   5+ years of experience as an Analytics Data Engineer or similar Data Science &amp; Analytics roles, preferably partnering with GTM and Product leads to build and report on key company-wide metrics.
  </li>
  <li>
   A passion for the company's mission of building helpful, honest, and harmless AI.
  </li>
  <li>
   Expertise in building multi-step ETL jobs, building robust data models through tooling like dbt; proficiency with workflow management platforms like Airflow and version control management tools through GitHub.
  </li>
  <li>
   Expertise in SQL and Python to transform data into accurate, clean data models.
  </li>
  <li>
   Experience building data reporting and dashboarding in visualization tools like Hex to serve multiple cross-functional teams.
  </li>
  <li>
   A bias for action and urgency, not letting perfect be the enemy of the effective.
  </li>
  <li>
   A &ldquo;full-stack mindset&rdquo;, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.
  </li>
  <li>
   Experience building an Analytics Data Engineering (or similar) function at start-ups.
  </li>
  <li>
   A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress.
   <br/>
   <br/>
  </li>
 </ul>
 The annual compensation range for this role is listed below.
 <br/>
 <br/>
 For sales roles, the range provided is the role&rsquo;s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
 <br/>
 <br/>
 <strong>
  Annual Salary
  <br/>
  <br/>
 </strong>
 $275,000&mdash;$370,000 USD
 <br/>
 <br/>
 <strong>
  Logistics
  <br/>
  <br/>
 </strong>
 <strong>
  Education requirements:
 </strong>
 We require at least a Bachelor's degree in a related field or equivalent experience.
 <br/>
 <br/>
 <strong>
  Location-based hybrid policy:
 </strong>
 Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
 <br/>
 <br/>
 <strong>
  Visa sponsorship:
 </strong>
 We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
 <br/>
 <br/>
 <strong>
  We encourage you to apply even if you do not believe you meet every single qualification.
 </strong>
 Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
 <br/>
 <br/>
 <strong>
  Your safety matters to us.
 </strong>
 To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.
 <br/>
 <br/>
 <strong>
  How We're Different
  <br/>
  <br/>
 </strong>
 We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
 <br/>
 <br/>
 The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
 <br/>
 <br/>
 <strong>
  Come work with us!
  <br/>
  <br/>
 </strong>
 Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
 <strong>
  Guidance on Candidates' AI Usage:
 </strong>
 Learn about our policy for using AI in our application process
</div>


Analytics Data Engineer

VNS Health

<div>Overview: The SciTech organization at VNS Health is seeking an experienced Analytics Data Engineer to join our team. This hybrid role combines data engineering and analytics engineering &ndash; with the ideal candidate working end to end on ingestion, transformation, and data modeling workflows to power VNS's advanced analytics and machine learning products. The Data Analytics Engineer will initially focus on developing the Care Transitions Platform, ensuring reliable ingestion and transformation of claims and membership data for downstream analytics and ML scoring. Responsibilities:
<p><b>
What We Provide</b></p><ul><li>
Referral bonus opportunities
</li><li>Generous paid time off (PTO), starting at 30 days of paid time off and 9 company holidays
</li><li>Health insurance plan for you and your loved ones, Medical, Dental, Vision, Life and Disability
</li><li>Employer-matched retirement saving funds
</li><li>Personal and financial wellness programs
</li><li>Pre-tax flexible spending accounts (FSAs) for healthcare and dependent care
</li><li>Generous tuition reimbursement for qualifying degrees
</li><li>Opportunities for professional growth and career advancement
</li><li>Internal mobility, generous tuition reimbursement, CEU credits, and advancement opportunities</li></ul><p><b>
What You Will Do</b></p><ul><li>
Develop and orchestrate scalable ETL/ELT processes using AWS B2B Data Interchange, Glue, Step Functions, and Redshift, ensuring data integrity, reliability, and performance.</li><li>
Apply advanced knowledge of healthcare data standards (e.g. EDI 834/835/837, FHIR) to build compliant data interfaces.</li><li>
Implement automated data quality checks and validation processes to ensure completeness and accuracy of raw and transformed healthcare data.</li><li>
Collaborate with data scientists and analysts to design clean, reusable, and well-documented data marts that support ML pipelines and other advanced analytics, including Generative AI and large language model applications.</li><li>
Implement, document, and deploy data marts to Redshift and Snowflake using dbt.</li><li>
Manage source control, testing, and deployment using GitLab CI/CD, supporting collaborative, version-controlled data development.</li><li>
Apply Infrastructure as Code (IaC) and DevOps principles to automate and scale data pipeline deployment across environments.</li><li>
Support and enhance the data pipelines powering VNS Commercial Analytics products, ensuring consistent service levels.</li><li>
Work collaboratively within an agile development environment, participating in sprint planning, code reviews, and backlog grooming.</li><li>
Ensure compliance with data security, privacy, and governance standards, particularly those applicable to PHI and HIPAA.</li><li>
Participates in special projects and performs other duties as assigned.</li></ul>
Qualifications:
<p><b>
Licenses and Certifications:</b>
<br>
AWS Certified Data Engineer preferred
<br>
<br>
<b>Education:
</b><br>
Bachelor's Degree in Computer Science, Statistics, Informatics, Information Systems or a related field required Master's Degree preferred<br>
<br>
<b>Work Experience:</b></p><ul><li>
Three plus years in data engineering, analytics engineering, or equivalent experience required Experience building robust ETL/ELT pipelines that conform to industry data standards (e.g., HL7, X12), for healthcare or a related sector (e.g., finance, insurance) required</li><li>
Advanced SQL skills and experience with data modeling concepts (SCDs, normalization, dimensional modeling) required</li><li>
Proficiency in Python (for data manipulation, automation, or orchestration) required</li><li>
Experience with Git-based collaboration and CI/CD automation (preferably GitLab CI) required</li><li>
Experience with cloud data engineering (AWS, GCP, or Azure), with a preference for prior AWS Data Engineering experience (e.g., using S3, Glue, Lambda, Step Functions, Redshift) required</li><li>
Experience working in agile environments with cross-functional data teams required</li><li>
Familiarity with data governance, role-based access controls (RBAC), and HIPAA compliance preferred Significant experience working with healthcare data in industry preferred</li><li>
Standard formats (HL7, X12), and familiarity with healthcare data sources (e.g., EMR data, claims) preferred</li></ul>
Pay Range: USD $98,200.00 - USD $130,800.00 /Yr.</div>

Senior Engineer, Data Analytics Warehousing

NVIDIA

<div><div><div>NVIDIA&rsquo;s Hardware Infrastructure organization is seeking a Senior Data Engineer to build and evolve analytics-ready data platforms that power observability, reliability analysis, and capacity forecasting for EDA datacenters. In this role, you will focus on transforming large-scale observability and telemetry data into trusted, well-modeled datasets that enable data scientists, analysts, and engineers to drive insights across global CPU and GPU compute clusters. We work closely with observability, infrastructure, and data science teams to ensure that data from EDA workloads and datacenter hardware is high quality, accessible, and optimized for analytical and predictive use cases.</div><div></div><div>
What You&rsquo;ll Be Doing:</div><ul><li><div>
Design, build, and maintain analytics-focused data pipelines that ingest, transform, and curate observability data from EDA datacenters</div></li><li><div>
Develop reliable ingestion pipelines for metrics, logs, traces, and hardware health telemetry generated by large-scale CPU and GPU clusters</div></li><li><div>
Partner with observability engineers to integrate data from tools such as Prometheus, Grafana, Elastic/OpenSearch, and Spark-based platforms into unified analytical datasets</div></li><li><div>
Model and organize data to support exploratory analysis, reliability modeling, forecasting, and long-term trend analysis</div></li><li><div>
Build and optimize batch and streaming workflows that support both near-real-time analytics and historical analysis</div></li><li><div>
Implement data quality checks, validation frameworks, and monitoring to ensure analytical accuracy and consistency</div></li><li><div>
Define data retention, aggregation, and enrichment strategies that balance analysis needs, system performance, and storage costs</div></li><li><div>
Enable self-service analytics by improving data discoverability, documentation, and usability</div></li><li><div>
Collaborate with data scientists and analysts to understand analytical requirements and evolve datasets to support new models and insights</div></li><li><div>
Continuously improve pipeline scalability, reliability, and performance as datacenter footprint and workload complexity grow</div></li></ul><div></div><div>
What We Need to See:</div><ul><li><div>
MS (preferred) or BS in Computer Science (or equivalent experience) or a related field with at least 10+ years of experience designing, building, and operating large-scale data pipelines and data platforms for distributed systems or infrastructure data</div></li><li><div>
Proficiency in Python and SQL, with experience supporting analytical and exploratory workloads</div></li><li><div>
Hands-on experience with distributed data processing frameworks such as Spark or similar technologies</div></li><li><div>
Familiarity working with observability and telemetry data, including metrics, logs, traces, and time-series data</div></li><li><div>
Experience designing data models and schemas that support flexible analysis and forecasting</div></li><li><div>
Ability to take ownership of data engineering initiatives and drive them end-to-end in collaboration with multi-functional partners</div></li><li><div>
Experience implementing data quality, validation, and monitoring for analytics pipelines</div></li><li><div>
Strong communication and collaboration skills, particularly when collaborating with engineering and infrastructure teams</div></li><li><div>
Adaptability in fast paced environments with evolving analytical and operational needs</div></li></ul><div></div><div>
Ways to Stand Out from the Crowd:</div><ul><li><div>
Experience supporting datacenter infrastructure analytics, hardware reliability programs, or workload performance analysis</div></li><li><div>
Familiarity with EDA workflows, HPC environments, or GPU-accelerated compute platforms</div></li><li><div>
Experience integrating or operating observability stacks (Prometheus, Grafana, Elastic/OpenSearch, Kafka, Spark, or similar tools)</div></li><li><div>
Background in large-scale distributed systems or data platforms</div></li><li><div>
A track record of improving analytics velocity and reliability through better data foundations</div></li></ul></div><div></div>
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.<div></div><div><div><div><div><div><div><div><div>
You will also be eligible for equity and <div>benefits</div>.</div></div></div></div></div></div></div></div><div></div>
Applications for this job will be accepted at least until March 21, 2026.<div></div><div>
This posting is for an existing vacancy.</div><div>
NVIDIA uses AI tools in its recruiting processes.</div><div></div>
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.</div><div></div>

Senior Data Engineer - EDA Datacenter Analytics and Observability

Data Engineer, Product Analytics

NiCE

<div><div><p>At NiCE, we don't limit our challenges. We challenge our limits. Always. We're ambitious. We're game changers. And we play to win. We set the highest standards and execute beyond them. And if you're like us, we can offer you the ultimate career opportunity that will light a fire within you.</p></div><p></p>
<p><b>
So, what's the role all about?</b></p>
<p>
As a NiCE <b>AI Data Engineer</b> you are responsible for supporting the use of the NiCE Interaction Analytics (NIA) product suite to prove out business use cases as part of Proofs of Concepts (POCs). The POC is used to support the NiCE sales efforts to demonstrate the value of the NIA product suite. In this capacity, you will work with the NiCE sales team to obtain unstructured Customer Experience (CX) interactions (audio, chats, emails, social media, etc.) from customers and transform the interactions into a format that can be processed by the NIA product suite. You will act as an Interaction Analytics data expert who understands key data development and the impact of downstream cases and value to be derived from having data generated from unstructured interactions. You will partner closely with the Customer Engagement Analytics (CEA) Research, Product and Services teams blending your data expertise with best-in-class technology advancements and client insights to accomplish the team's objectives.</p>
<p>
AI Data Engineers are experts in the value derived from unstructured CX interactions. It is that expertise, along with technical fluency, that allow the Business Consulting team to build scalable, out of the box data structures that reveal operational and measurable outcomes. The responsibilities for this role includes the development of the underlying data structures, along with the ability to understand new and evolving client requests for improvement and the ability to incorporate those needs into a successful build and execution plan for each POC.</p>
<p>
The ideal candidate is intellectually inquisitive, with strong communication, organization, analytical and technical capabilities. As a self-starter, they are not afraid to roll up their sleeves to learn and validate evolving toolsets while maintaining focus on what success looks like with our ultimate goals for data solutions. As they gain and maintain system and data expertise, the roll will continue to open up for direct client interactions, feedback capture and build plans.</p>
<p><b>
How will you make an impact?</b></p>
<ul>
<li>Serve as the focal point for managing the delivery of CX interactions and corresponding metadata utilizing various data delivery methods.</li>
<li>Serve as the focal point for the development of pre-defined data structures for automated analysis of large sets of CX interactions across all channels (audio, chat, email, social, etc.). This includes:
<ul><li>Manipulation of CX interaction metadate into approved formats</li>
<li>Manipulation of CX interactions into the NiCE Interaction Analytics platform</li>
<li>Manipulation of CX transcripts</li>
</ul></li><li>Utilize evolving tools from Research that support the development of the data structures.</li>
<li>Provide feedback to the Research and Product teams on how we continue to evolve tooling and data integration with CEA products.</li>
<li>Work with client requirements to understand new requests and how we can or cannot meet them.</li>
<li>Some team members may work directly with clients as a Subject Matter Expert to discuss data solutions, expectations and best practices.</li>
<li>Educate field teams (Consulting and Customer Success) on data solutions, definitions, best practices, etc.</li>
<li>Provide input on the use of developed data models for both Product and Field teams to optimize the use of developed data assets.</li>
<li>As the Enlighten AI team is focused on Data Innovation, team members may be asked to support other projects, solutions and/or deployments using other Enlighten AI solutions.</li>
<li>Manage the utilization of the CX Proof of Concept (POC) VM servers.</li>
</ul>
<p><b>Have you got what it takes?</b></p>
<ul>
<li>3+ years of software engineering experience <i>and/or</i> significant experience with business intelligence, analytics, and data visualization as a services provider</li>
<li>Experience using Windows Server</li>
<li>Experience with basic scripting in PowerShell, Command Line, or Python</li>
<li>Knowledge of SQL preferred, such as using Data Manipulation Language and Data Definition Language</li>
<li>Familiarity with Linux</li>
<li>Familiarity with ssh and basic bash skills</li>
<li>Experience with Docker, accessing AWS S3 buckets, and SFTP</li>
<li>Experience with use of technology to build and analyze datasets for operational outcomes</li>
<li>Excellent oral and written communication skills in English</li>
<li>Ability to multi-task and meet deadlines when supporting requests that create competing priorities</li>
<li>Ability to develop and maintain good working relationships with cross-functional teams</li>
<li>Ability to communicate comfortably across all levels of corporate structure</li>
<li>Demonstrated ability to take the initiative and work in a self-directed manner</li>
<li>Ability to thrive in a changing environment</li>
</ul>
<p><b>What's in it for you?</b></p>
<p>
Join an ever-growing, market disrupting, global company where the teams &ndash; comprised of the best of the best &ndash; work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!</p>
<p><b>
Requisition ID: </b>10299<br>
<b>Reporting into: </b>Vice President of Solution Sales<br>
<b>Role Type: </b>Individual Contributor</p>
<p></p><div><p><b><i>
About NiCE
</i></b></p><p><i>NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions.
</i></p><p><i>Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.
</i></p><p><i>NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.</i></p></div></div><p></p>

AI Data Engineer

RevSpring, Inc

<div><div><b>Job Title: Senior Data Engineer - Analytics</b></div>
<div></div><div><b>Essential Functions:</b></div>
<ul><li>Collaborate with other internal teams to design data pipelines to ingest information from various systems to our BigQuery or Redshift data warehouse</li>
<li>Take ownership of the codebase, identifying gaps, areas for improvement, refactoring where needed, and keeping the design fresh and modern</li>
<li>Actively code to unblock technical and communication challenges as necessary to ensure teams meet product roadmaps and close those gaps.</li>
<li>Participate in architecture review decisions, designs, and documentation that will govern the direction of the team, the codebase, and multiple products over a several month timeframe</li>
<li>Communicate effectively with stakeholders (upper management, engineering manager, product manager, and peers) regarding the product you are responsible for</li>
<li>Provide feedback and participate in pair programming exercises.</li>
</ul>
<div></div><div><b>Success in this role:</b></div>
<ul><li>Team delivers reliable, scalable, high performing customer facing analytic services within analytic SLAs</li>
<li>Team consistently delivers committed business initiatives and coordinates with other stakeholders to roll out products with analytic insights.</li>
<li>Business teams and Customers are empowered with AI assisted insights without dependency on engineering</li>
<li>Consistently deliver high quality code that is easily maintained and scaled. Your work is reliable and your team members and stakeholders fully trust you to execute your responsibilities with minimal oversight</li>
<li>Contribute to the team culture where innovation, autonomy, and accountability thrive</li>
</ul>
<div></div><div><b>Minimum Requirements:</b></div>
<div><b>Specific Job Skills:</b></div>
<div></div><ul><li>Ability to approach complex, ambiguous data challenges systematically. You can diagnose the problem, come up with a plan to address it, and see that plan through.</li>
<li>Experience owning data integrity, ensuring that data is reliable, timely, and traceable from source to consumption</li>
<li>Experience creating and maintaining Extract, Transform, and Load (ETL) Pipelines and using modern ETL tools such as Python, SQL, Airflow, DBT, S3, Airbyte, Confluent.</li>
<li>Experience creating and maintaining analytic semantic layers and business intelligence dashboard such as Looker, PowerBI, Tableau, etc.</li>
<li>Experience owning data integrity, ensuring that data is reliable, timely, and traceable from source to consumption</li>
<li>Proficiency in leveraging AI agents and other AI tools to significantly enhance developer productivity.</li>
<li>Experience working with database and data warehouse technologies such as Postgres, Bigquery, and Redshift.</li>
<li>Experience with cloud services such as AWS, Azure, GCP.</li>
<li>Experience in developing large scale data models and complex data pipelines.</li>
</ul>
<div></div><div><b>Preferred Skills:</b></div>
<ul><li>Preferred: Experience in working with large slow changing dimension data models</li>
<li>Preferred: Experience in the US healthcare system, in particular with data systems and EHRs such as Epic, Cerner or Athenahealth.</li>
</ul><div><b>Education:</b> BS Degree or equilivent work experience</div>
<div><b>Experience:</b> Five years experience developing data platforms using Python, SQL</div>
<div><b>Supervision:</b> N/A</div>
<div><b>Certifications:</b> N/A</div>
<div><b>Language Skills:</b></div>
<div>Ability to read, analyze and interpret general business periodicals, professional journals, technical procedures or governmental regulations. Ability to write reports, business correspondence and procedure manuals. Ability to effectively present information and respond to questions from a variety of both internal and external sources.</div>
<div></div><div><b>Physical Capabilities: Standard categories</b></div>
<div>The physical capabilities described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.</div>
<div></div><div>While performing the duties of this job, the employee is regularly required to sit; use hands to finger, handle, or feel; reach with hands and arms; and talk or hear. The employee is occasionally required to stand and walk. The employee must occasionally lift and/or move up to 10 pounds. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception, and ability to adjust focus.</div>
<div></div><div>RevSpring is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.</div>
<div></div><div><b>Note:</b> This Job Description may not describe all of the job responsibilities and standards assigned to this position. The duties may change from time to time. RevSpring does not discriminate against any group in hiring or employment practices. Nothing in this job description constitutes a contract for employment.</div></div>

Senior Data Engineer - Analytics

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