big data engineer

DS Technologies Inc

<div><div><div>About US: We are a company that provides innovative, transformative IT services and solutions. We are passionate about helping our clients achieve their goals and exceed their expectations. We strive to provide the best possible experience for our clients and employees. We are committed to continuous improvement and innovation, and we are always looking for ways to improve our services and solutions. We believe in working collaboratively with our clients and employees to achieve success.</div>
<div></div>
<div>DS Technologies Inc is looking for Engineer II &ndash; Big Data / ETL Engineer (Apptio) role for one of our premier clients. 
</div><div>Job Title: Engineer II &ndash; Big Data / ETL Engineer (Apptio) 
Location: New York, NY (NYC Metro Area only)(Hybrid) 
Position Type: Contract 
Only W2 
 
Job Summary: 
We are looking for a highly skilled Big Data / ETL Engineer who can work as a standalone developer and write production-ready code from scratch. The ideal candidate has strong expertise in Python, SQL, ETL development, and data warehousing, with hands-on experience building scalable data pipelines in enterprise environments. 
 
Key Responsibilities:
</div><ul><li>Design, develop, and maintain ETL pipelines using Python from scratch</li>
<li>Write efficient, reusable, and scalable code following OOP principles</li>
<li>Develop and optimize complex SQL queries, stored procedures, and database objects</li>
<li>Perform data modeling including schemas and entity relationships</li>
<li>Build and manage Airflow DAGs</li>
<li>Ingest, cleanse, govern, and report data from Big Data platforms</li>
<li>Work with multiple SQL dialects (SQL Server, Oracle, DB2, PostgreSQL)</li>
<li>Collaborate with stakeholders while operating independently</li>
</ul><div>Required Skills &amp; Qualifications:</div>
<ul><li>Strong Python (ETL pipeline development from scratch)</li>
<li>Expert SQL and RDBMS concepts</li>
<li>MS SQL Server (SSIS, SSRS)</li>
<li>Oracle PL/SQL</li>
<li>Solid understanding of OOP principles</li>
<li>Apptio experience</li>
<li>Airflow (DAG development)</li>
<li>Experience with Data Warehousing &amp; Big Data</li>
<li>Node.js, JSON, and NoSQL databases</li>
<li>Ability to work as an independent contributor</li>
<li>Must be local to NYC metro area</li>
</ul><div>Nice to Have:</div>
<ul><li>PySpark / Apache Spark</li>
<li>Databricks Delta Lakehouse or BigQuery</li>
<li>Exposure to cloud-based business tools and platforms</li>
</ul>
</div>Flexible work from home options available.</div>

Engineer II – Big Data / ETL Engineer (Apptio)

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
Amazon Web Services (AWS) is a dynamic and rapidly growing business within Amazon and the leader in providing secure, reliable, scalable, and innovative services that help over a million businesses, governments, education, and not for profits across the globe scale and grow! AWS provides a wide set of scalable services to meet customer needs. 
 
At AWS, the Global Deal Strategy and Programs (GDSP) team drives cloud adoption and business growth through innovative pricing strategies. The organization comprises two specialized teams: Strategic Customer Engagements, which guide ** transformative deals with industry leaders, and Private Pricing Programs &amp; Experiences, which scales and optimizes pricing solutions across our diverse customer base. Within GDSP, you will develop deep expertise in cloud economics, hone your strategic thinking, and directly impact AWS's market leadership while working with latest technologies and global clients. 
 
The AWS Global Deal Strategy and Programs (GDSP) organization is responsible for the Private Pricing Program. The Private Pricing Analytics and Insights (PPA&amp;I) team owns building scalable analytical solutions that enable the GDSP organization with actionable insights to make data-driven decisions. This role will focus on Data Engineering, and Analytics related to the Private Pricing Program, requiring deep technical skills, strong business acumen and a deep analytical background to provide actionable data-driven insights and decision support. 
 
As a Data Engineer on this team, you will drive efficiency in data handling processes, setup product analytics, drive advanced analysis and build new metrics which are key inputs to improve the health, scale and growth of the Private Pricing Program. You will work collaboratively with the business leaders operations, and engineering teams on many non-standard and unique business problems and support business initiatives by collecting required and related data from external/internal sources. 
 
The ideal candidate should have strong communication skills and ability to prioritize effectively to ensure timelines are met. You will own projects from engaging with customers to production and delivery of a suite of tools used by the organization to make key business decisions. You should be a self-starter, comfortable with ambiguity, able to think big and be creative (while still paying careful attention to detail). You think in terms of architecture, not just code. You proactively work to improve the consistency and integration between your team&rsquo;s BI solutions and any related systems or artifacts. 
 
Key job responsibilities 
Design, develop, and maintain scalable data solutions for metrics, reports, analyses, and dashboards that support analytical and business needs 
 
Collaborate with technology teams to extract, transform, and load data from diverse sources using AWS services and internal tools 
Build and deliver high-quality datasets that support data science initiatives and customer reporting requirements 
 
Automate and optimize reporting processes to enable self-service analytics for stakeholders 
Translate business problem statements into technical analysis requirements 
 
Apply analytical and statistical rigor to answer business questions and drive data-driven decisions 
Develop measurement frameworks that quantify customer experience and drive business outcomes 
 
Create queries and visualizations for ad-hoc requests, projects, and ongoing reporting needs 
Write efficient, optimized queries with deep knowledge of data structures and query optimization techniques 
 
Adopt best practices in reporting and analysis including data integrity, design, validation, and documentation 
 
Troubleshoot operational data quality issues and audit existing data pipelines and queries 
 
Recommend improvements to back-end data sources for increased accuracy and simplicity<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>3+ years of data engineering experience</li><li>1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience</li><li>1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience</li><li>1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience</li><li>1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience</li><li>1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience</li><li>Experience with data modeling, warehousing and building ETL pipelines</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions</li><li>Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, NY, New York - 145,300.00 - 196,600.00 USD annually 
USA, TX, Austin - 132,100.00 - 178,800.00 USD annually 
USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually</div>

Data Engineer, AWS GDSP A&I

BlackRock

<div>
 
 About This Role
 
 
 
 <ul>
 <li>
 Improve BlackRock&rsquo;s ability to enhance our retail sales distribution capabilities and services suite by creating, expanding and optimizing our data and data pipeline architecture.
 </li>
 <li>
 You will create and operationalize data pipelines to enable squads to deliver high quality data-driven product.
 </li>
 <li>
 You will be accountable for managing high-quality datasets exposed for internal and external consumption by downstream users and applications.
 </li>
 <li>
 Top technical / programming skills &ndash; Python, Java and Scala with ability to work across big data frameworks such as Spark, Hadoop Suite, PySpark, Hive, Cloud Data Platforms Preferably Snowflake and SQL.  Experience working with flat files (e.g., csv, tsv, Excel), Database API sources is a must to both ingest and create transformations.
 </li>
 <li>
 Given the highly execution-focused nature of the work, the ideal candidate will roll up their sleeves to ensure that their projects meet deadlines and will always look for ways to optimize processes in future cycles.
 </li>
 <li>
 The successful candidate will be highly motivated to create, optimize, or redesign data pipelines to support our next generation of products and data initiatives.
 </li>
 <li>
 You will be a builder and an owner of your work product.
 
 
 </li>
 </ul>
 Responsibilities:
 
 
 <ul>
 <li>
 Lead in the creation and maintenance of optimized data pipeline architectures on large and complex data sets.
 </li>
 <li>
 Assemble large, complex data sets that meet business requirements.
 </li>
 <li>
 Act as lead to identify, design, and implement internal process improvements and relay to relevant technology organization.
 </li>
 <li>
 Work with stakeholders to assist in data-related technical issues and support their data infrastructure needs.
 </li>
 <li>
 Automate manual ingest processes and optimize data delivery subject to service level agreements; work with infrastructure on re-design for greater scalability.
 </li>
 <li>
 Keep data separated and segregated according to relevant data policies.
 </li>
 <li>
 Demonstrated ability to join a complex global team, collaborate crossfunctionally (data scientists, platform engineers, business stakeholders), and take ownership of major components of the data platform ecosystem and develop data ready tools to support their job.
 </li>
 <li>
 Be up-to-date with the latest tech trends in the big-data space and recommend them as needed.
 </li>
 <li>
 Identify, investigate, and resolve data discrepancies by finding the root cause of issues; work with partners across various cross-functional teams to prevent future occurrences.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Overall 4+ years of hands-on experience in computer/software engineering with majority in big data engineering.
 </li>
 <li>
 4+ years of strong Python or Scala programming skills (Core Python and PySpark) including hands-on experience creating and supporting UDFs and modules like pytest.
 </li>
 <li>
 4+ years of experience with building and optimizing &lsquo;big data&rsquo; pipelines, architectures, and data sets. Familiarity with data pipeline and workflow management tools (e.g., Airflow, DBT, Kafka).
 </li>
 <li>
 4+ years of hands-on experience on developing on Spark in a production environment. Expertise on parallel execution, deciding resources and different modes of executing jobs is required.
 </li>
 <li>
 4+ years of experience using Hive (on Spark), Yarn (logs, DAG flow diagrams), Sqoop. Proficiency bucketing, partitioning, tuning and handling different file formats (ORC, PARQUET &amp; AVRO).
 </li>
 <li>
 4+ years of experience using Transact SQL (e.g., MS SQ Server, MySQL), No-SQL and GraphQL.
 </li>
 <li>
 Strong experience implementing solutions on Snowflake
 </li>
 <li>
 Experience with data quality and validation frameworks, especially Great Expectations for automated testing.
 </li>
 <li>
 Strong understanding and use of Swagger/OpenAPI for designing, documenting, and testing RESTful APIs.
 </li>
 <li>
 Experience in deployment, maintenance, and administration tasks related to Cloud (AWS, Azure Preferred), OpenStack, Docker, Kafka and Kubernetes. Familiarity with CI/CD pipelines for data pipeline automation and deployment (Jenkins, GitLab CI, Azure DevOps)
 </li>
 <li>
 Experience with data governance, metadata management, and data lineage using tools like Axon and Unity Catalog. Expertise in managing business glossaries, data access control, auditing, and ensuring centralized governance across data assets in both cloud and hybrid environments.
 </li>
 <li>
 Hands-on experience with Databricks, including notebooks, workflows, and ML integrations.
 </li>
 <li>
 Experience with working with global teams across different time zones
 </li>
 <li>
 Plus - Experience with Machine Learning and Artificial Intelligence
 </li>
 <li>
 Plus - Experience with Generative Artificial Intelligence
 
 
 </li>
 </ul>
 For New York, NY Only the salary range for this position is USD$132,500.00 - USD$162,000.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.
 
 
 
 Our Benefits
 
 
 
 To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
 
 
 
 Our hybrid work model
 
 
 
 BlackRock&rsquo;s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person &ndash; aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.
 
 
 
 About BlackRock
 
 
 
 At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children&rsquo;s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.
 
 
 This mission would not be possible without our smartest investment &ndash; the one we make in our employees. It&rsquo;s why we&rsquo;re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.
 
 
 For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | LinkedIn: www.linkedin.com/company/blackrock
 
 
 BlackRock is proud to be an equal opportunity workplace. We are committed to equal employment opportunity to all applicants and existing employees, and we evaluate qualified applicants without regard to race, creed, color, national origin, sex (including pregnancy and gender identity/expression), sexual orientation, age, ancestry, physical or mental disability, marital status, political affiliation, religion, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law.
 
 View the
 
 
 EEOC&rsquo;s Know Your Rights poster and its supplement
 
 
 and the
 
 
 pay transparency statement.
 
 
 
 BlackRock is committed to full inclusion of all qualified individuals and to providing reasonable accommodations or job modifications for individuals with disabilities. If reasonable accommodation/adjustments are needed throughout the employment process, please email Disability.Assistance@blackrock.com. All requests are treated in line with our
 
 privacy policy
 
 .
 
 
 BlackRock will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance law.
</div>

Data Engineer, Associate

The Phoenix Group

<div>
 
 
 Position Summary
 
 
 
 The team is looking to add a Sr. Data Engineer who will be instrumental in building and supporting the data infrastructure behind client-facing financial insights.
 
 
 
 
 
 
 What You&rsquo;ll Be Doing
 
 
 <ul>
 <li>
 Architect and maintain scalable data workflows that handle high-volume, complex datasets from ingestion through delivery
 </li>
 <li>
 Explore and interpret data to uncover trends, anomalies, and opportunities that inform client strategies
 </li>
 <li>
 Identify and resolve inconsistencies in data, ensuring high standards of accuracy and reliability
 </li>
 <li>
 Continuously refine system performance and improve existing data processes
 </li>
 <li>
 Build and enhance ETL pipelines using Python, while writing efficient, high-performing SQL queries
 </li>
 <li>
 Manage and optimize database operations across MySQL and Microsoft SQL Server environments
 </li>
 <li>
 Partner with stakeholders across teams to design data structures that support evolving business needs while adhering to strict data governance standards
 </li>
 </ul>
 
 
 Core Qualifications
 
 
 <ul>
 <li>
 Degree in a technical or quantitative field such as Computer Science, Engineering, Mathematics, or similar
 </li>
 <li>
 Hands-on experience developing and supporting data pipelines in production environments
 </li>
 <li>
 Strong programming ability in Python and advanced SQL expertise
 </li>
 <li>
 Solid understanding of relational database design, performance tuning, and query optimization (MySQL, SQL Server)
 </li>
 <li>
 Analytical mindset with a high level of precision and the ability to manage competing priorities
 </li>
 </ul>
 
 
</div>

Data Engineer

Sunset

<div>
 
 About Sunset
 
 
 
 Sunset is building the data layer for real-world AI training. We work with frontier labs to turn messy, multi-modal enterprise data into the highest-quality training data on the market &mdash; sourced from the hundreds of venture-backed startups we've helped wind down.
 
 
 We're a fast-growing team based in-person in Dumbo, Brooklyn. Backed by Floodgate, Afore Capital, Hustle Fund, and incredible entrepreneurs.
 
 
 
 The Role
 
 
 
 As a Data Engineer at Sunset, you'll own the pipeline that turns raw, chaotic enterprise data into the highest-quality training data on the market. One of our core technical challenges is entity resolution and de-identification across different sources and modalities. An even deeper challenge is understanding the node structures and linkages well enough to effectively reconstruct the business world this data comes from. All of this happens on sensitive data, which means security and privacy aren't a separate workstream but are built into every pipeline, system, and decision we make.
 
 
 
 What You'll Work On
 
 
 
 You'll own problems end-to-end. Some examples of what you might tackle in your first 90 days:
 
 
 <ul>
 <li>
 Designing the de-identification layer that replaces PII with stable pseudonyms while preserving every relationship across every source
 </li>
 <li>
 Building coreference resolution across Slack threads, email chains, and Linear comments so that "me," "him," and first-name mentions all resolve to the right canonical entity
 </li>
 <li>
 Hardening how we ingest, store, and process sensitive client data &mdash; from encryption and access controls to audit trails and isolation boundaries
 </li>
 <li>
 Extending our entity resolution pipeline to handle new modalities &mdash; think audio, video, design files, or embedded references inside documents
 
 
 </li>
 </ul>
 
 You Might Be a Fit If
 
 
 
 <ul>
 <li>
 You are a product minded engineer and have shipped data pipelines at scale
 </li>
 <li>
 You have strong Python and are comfortable across NER, record linkage, and coreference
 </li>
 <li>
 You take security and privacy seriously and have built systems where getting it wrong wasn't an option
 </li>
 <li>
 You want to own a hard, ambiguous problem end-to-end rather than wait for a PRD
 </li>
 <li>
 AI is deeply integrated into your workflow and life
 
 
 </li>
 </ul>
 
 This Role Might Not Be a Fit If
 
 
 
 <ul>
 <li>
 You want to work remote or hybrid &mdash; we're in-person 5 days/week in Dumbo
 </li>
 <li>
 You want to do novel ML research &mdash; this role is applied, not research
 </li>
 <li>
 You prefer long planning cycles or narrow ownership
 
 
 </li>
 </ul>
 
 Our Stack
 
 
 
 Python, Postgres, Redis, AWS. We pick tools based on the problem, not the other way around.
 
 
 
 Compensation &amp; Benefits
 
 
 
 <ul>
 <li>
 $180K&ndash;$280K base + meaningful equity
 </li>
 <li>
 100% covered medical, dental, and vision
 </li>
 <li>
 Unlimited PTO
 </li>
 <li>
 $500 in-office setup allowance
 
 
 </li>
 </ul>
 
 How We Hire
 
 
 
 <ul>
 <li>
 Intro Chat (20 min) &ndash; mutual fit and interests
 </li>
 <li>
 Technical Session (1hr) &ndash; collaborative problem-solving
 </li>
 <li>
 Onsite (2&ndash;3 hrs) &ndash; product deep dive, system design, meet the team
 </li>
 <li>
 Quick references &rarr; Offer
 
 
 </li>
 </ul>
 Compensation Range: $180K - $280K
 
 
</div>

Apple

At Apple, we work every day to create products that enrich people&rsquo;s lives. Our Advertising Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads in App Store and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy. 
 
Ads Experimentation team is seeking a Machine Learning Engineer and Data Engineer who will help drive innovation. This is a hands-on role for developing &amp; supporting a state of the art ads experimentation platform. This role requires partnering with cross-functional teams to effectively coordinate the complex interdependencies inherent in application development. A successful candidate has strong technical skills and is eager to create intuitive user experiences; they have a keen eye for the details that surprise and delight our customers. While understanding our product features, you will perform rigorous analyses, measure performance and make data-driven decisions and develop scalable tools that facilitate quick and accurate decision making. 
 
Description 
 
Design and build a new generation of experimentation platform for the Ads Platform organization. Apply leading-edge technologies to enable safe and data driven launch of features that help connect Apple users and advertisers while delivering on Apple's privacy commitment through experimentation. Collaborate with stakeholders and data scientists to design experiments and statistical methods that account for the marketplace dynamics and yield reliable treatment effects. 
 
Provide expert technical guidance to engineers and scientists on data engineering and monitoring techniques. 
 
You will join and contribute to a culture that emphasizes observability and understandability, reliability, resiliency, simplicity, reusability, extensibility, scalability, velocity and productivity. We are one team, nurturing each other&rsquo;s growth and supporting each other in delivering for our customers and Apple. 
 
&quot;,&quot;responsibilities&quot;:&quot; 
 
Preferred Qualifications 
 
Advanced Degree in Computer Science, Applied Math or related engineering field. 
 
8+ years of industry experience building scalable applications and data pipelines 
 
Minimum Qualifications 
 
8+ years of experience in software and data engineering and analysis with an in-depth understanding of SQL and spark. Industry experience in SDLC is preferred. 
 
Analysis: Conduct rigorous, end-to-end analyses using SQL, Python, and statistical methods to uncover insights and improve treatment effect estimates. 
 
Experience with A/B testing infrastructure and methodologies and understanding of the assumptions of randomized control trials. Experience in A/B testing and/or ad tech systems is a bonus. 
 
Proficiency in SQL and Pyspark or Scala to conduct analyses and build data products (pipelines and dashboards) to automate experiment reporting at scale. 
 
Lead the design, development, and maintenance of scalable and reliable data pipelines. Implement robust data quality checks, monitoring systems, and data lineage tracking. Advocate best practices for data engineering. Experience with using LLMs to build scaleable data Strategic Partnership: Work directly with stakeholders, including senior leaders, to identify, scope, and prioritise high-impact questions. 
 
Skilled at operating in a cross-functional organization. 
 
Ability to understand ambiguous and complex problems and design and execute analytical approaches and turn analysis into clear and concise takeaways that drive action. 
 
Curious business attitude with a proven ability to seek projects with a sense of ownership. 
 
Excellent communication, social and presentation skills. 
 
Desire to work in a fast-paced and challenging work environment. 
 
Mentor junior engineers and scientists on the team 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Staff Data Engineer - Experimentation

Adaptive Home Health

<div>
 
 About Us
 
 
 
 
 We are fixing US healthcare by building an AI-native physical care platform, starting with home health.
 
 
 
 Home health is a $140B industry with less than $10B in EBITDA &mdash; 40% of revenue is spent on pure administrative waste. We automate this work with AI, creating a fundamentally different cost structure compared to incumbents. This lets us rapidly take market share by serving the 30% of patients who go untreated today.
 
 
 
 By reshaping the cost structure of this industry, we unlock its growth.
 
 
 
 We&rsquo;ve built one of the best AI teams in the world (from Character AI, Scale, Palantir, Citadel, Jane Street) and paired them with a team of healthcare veterans and ex-MBB strategists to build a new type of healthcare company: one that delivers care at the speed of an AI company.
 
 
 Our physical care platform already operates with 30pp higher gross margins than traditional home health providers. With our AI advantage, we pay nurses more, remove their admin burden, and unlock the scale economics that have been missing from this fragmented industry. If we served this entire $140B market, instead of $10B in EBITDA, we&rsquo;d drive $60B.
 
 
 We're starting with home health, then expanding to all delivered care. Our mission is
 
 &ldquo;any care, any where&rdquo;
 
 .
 
 
 
 Fundamentally, our incentives are aligned with America. Every dollar in revenue we make is two dollars taken out of the healthcare system. If we succeed, so does US healthcare.
 
 
 
 
 About The Role
 
 
 
 We're hiring a
 
 Data Engineer
 
 to build the data infrastructure that powers business intelligence, operational analytics, and AI-driven decision-making across our platform. You'll design and implement data pipelines, integrate disparate healthcare data sources, and model complex domains like RCM, intake, and clinical operations to enable real-time insights and automation.
 
 
 A successful Data Engineer at Fira is
 
 analytical, detail-oriented, and comfortable working across the full data stack&mdash;from raw ingestion to analytics-ready models.
 
 You'll have significant ownership over our data architecture and the opportunity to define how we measure, monitor, and optimize every aspect of our operations.
 
 
 Over time, you'll take end-to-end ownership of our data platform, setting the technical vision for data infrastructure and enabling data-driven insights that shape product and business decisions.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and maintain robust data pipelines that integrate data from multiple sources including EMRs, EDI feeds, internal systems, and third-party APIs.
 </li>
 <li>
 Develop and manage data infrastructure using modern data stack technologies (Postgres, Databricks, Redshift, or similar warehouses).
 </li>
 <li>
 Model complex healthcare domains (RCM workflows, clinical operations, intake processes) into clean, queryable data schemas that support analytics and reporting.
 </li>
 <li>
 Build analytics, alerting, and dashboards to identify and prioritize opportunities for automation or process improvement across the business
 </li>
 <li>
 Contribute to the technical direction of our Business Intelligence platform, scaling data infrastructure to support growing operational needs.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Data Engineering Experience: 3+ years building and maintaining data pipelines, warehouses, and analytics infrastructure in a production environment.
 </li>
 <li>
 Technical Proficiency: Strong experience with SQL and at least one modern data warehouse (Databricks, Redshift, Snowflake, BigQuery) and relational databases (Postgres, MySQL).
 </li>
 <li>
 Analytics &amp; Data Science: Comfortable with statistical analysis, exploratory data analysis, and applying analytical techniques to solve business problems. Familiarity with Python or R for data analysis.
 </li>
 <li>
 Pipeline Development: Experience building ETL/ELT pipelines using modern orchestration tools (Airflow, dbt, Dagster, or similar).
 </li>
 <li>
 Collaboration &amp; Communication: Ability to translate technical data concepts for non-technical stakeholders and partner effectively with Product and Engineering teams.
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Experience in healthcare technology, especially with healthcare data standards (EDI, HL7, FHIR, claims data, clinical documentation).
 </li>
 <li>
 Experience with real-time or streaming data pipelines.
 </li>
 <li>
 Background in data science or machine learning, including feature engineering for AI/ML systems.
 </li>
 <li>
 Exposure to business intelligence tools (Hex, SigmaComputing, or similar).
 
 
 </li>
 </ul>
 
 What We Offer
 
 
 
 <ul>
 <li>
 Opportunity for growth in a fast-growing company
 </li>
 <li>
 Collaborative team valuing innovation and problem-solving
 </li>
 <li>
 Competitive salary and equity compensation
 </li>
 <li>
 Flexible time off policy&mdash;we expect most employees to take at least 3 weeks of vacation per year
 </li>
 <li>
 In-office lunches, dinners, and snacks to fuel your focus and well-being
 </li>
 <li>
 401(k) retirement plan with employer contribution
 </li>
 <li>
 Comprehensive health insurance, dental, and commuter benefits
 
 
 </li>
 </ul>
 
 Location
 
 
 
 This role is in-person 3-5 days a week in our New York City office
 
 
</div>

Explore 848+ Big data engineer in New York this April. Find roles across top companies and apply now to boost your career.

848 big data engineer jobs In New York

Engineer II – Big Data / ETL Engineer (Apptio)

Data Engineer, AWS GDSP A&I

Data Engineer, Associate

Data Engineer

Data Engineer

Staff Data Engineer - Experimentation

Data Engineer