Employment type in the employer’s posting: FULL_TIMEFrom the employer’s posting
Lead technically and develop engineers: Mentor engineers, lead architecture reviews, and take point on technical response to major incidents.
Enable analytics, reporting, and AI initiatives: Partner with analysts and data scientists to operationalize advanced analytics, predictive models, and AI use cases on top of the platform you build. Lead technically and develop engineers: Mentor engineers, lead architecture reviews, and take point on technical response to major incidents. Qualifications
8+ years in data or software engineering, including 5+ years focused on data platforms or big data
Strong experience architecting and operating data pipelines and data lakes
Experience designing and rolling out data governance frameworks covering quality, PII/PHI management, access control, and freshness monitoring
Experience designing orchestration strategy at platform level
Experience in healthcare, benefits, insurance, or another regulated industry a plus
Familiarity with distributed systems and microservices as data producers preferred
We serve employers, health plans, and health systems with data-driven solutions that reduce costs while actually improving health outcomes.
In the employer’s words · Read in context
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Day 14
Similar jobs usually come down between day 6 and day 54.
Well past Personify Health’s usual: its jobs come down by about day 4.
From 11,115 similar postings that came down, and 8 of Personify Health’s. Coming down is not always a hire.
6 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Experience designing orchestration strategy at platform level - Advanced SQL and strong Python proficiency - Apache Spark including performance tuning at scale preferred
Design and build large-scale pipelines: Integrate product systems, member and client data, claims and eligibility feeds, and third-party sources into a scalable, well-governed data platform. Own the open table format layer: Design and maintain the Iceberg or Delta Lake layer — including table design, partitioning, compaction, schema evolution, and long-term maintenance. Define and enforce governance standards: Build the platform’s governance framework covering data quality, PII/PHI classification and controls, freshness SLAs, and lineage — and hold the broader team to it.
- Deep, hands-on expertise in large-scale data transformation including performance tuning and cost optimization - Expert-level knowledge of open table formats: Apache Iceberg or Delta Lake - Strong experience architecting and operating data pipelines and data lakes
- Apache Spark including performance tuning at scale preferred - Apache Kafka and event-driven architecture experience preferred - Familiarity with distributed systems and microservices as data producers preferred
- Advanced SQL and strong Python proficiency - Apache Spark including performance tuning at scale preferred - Apache Kafka and event-driven architecture experience preferred
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New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Who We Are
Because health is personal. That's why Personify Health created the first and only personalized health platform—bringing health plan administration, holistic wellbeing solutions, and comprehensive care navigation together in one place. We serve employers, health plans, and health systems with data-driven solutions that reduce costs while actually improving health outcomes. Together, our team is on a mission to empower people to lead healthier lives.
Learn even more about the work that drives us at personifyhealth.com.
Ready To Architect and Build the Data Platform That Connects Every Product, Pipeline, and AI Initiative at Personify Health?
Why This Role Matters
Data Platform Engineering is a new organization with a clear mandate: make the handoff from product data to analytics insight reliable, governed, and invisible. As Lead Data Platform Engineer, you shape that from the ground up — designing the architecture, setting the standards, and shipping the pipelines that power reporting, AI use cases, and data-driven product features. This is a hands-on technical leadership role. You’ll set the direction and still write code.
What You'll Actually Do
Lead platform architecture and delivery: Own the end-to-end data platform — ingestion, lake layout, transformation layers, and serving — continuously improving reliability, performance, and scale.
Design and build large-scale pipelines: Integrate product systems, member and client data, claims and eligibility feeds, and third-party sources into a scalable, well-governed data platform.
Own the open table format layer: Design and maintain the Iceberg or Delta Lake layer — including table design, partitioning, compaction, schema evolution, and long-term maintenance.
Define and enforce governance standards: Build the platform’s governance framework covering data quality, PII/PHI classification and controls, freshness SLAs, and lineage — and hold the broader team to it.
Set engineering standards and orchestration patterns: Establish CI/CD, automated testing, monitoring, alerting, and orchestration standards that the team adopts and operates against.
Define data contracts with product teams: Set standards for how product delivery teams produce data and influence their services to make downstream consumption cleaner and more reliable.
Enable analytics, reporting, and AI initiatives: Partner with analysts and data scientists to operationalize advanced analytics, predictive models, and AI use cases on top of the platform you build.
Lead technically and develop engineers: Mentor engineers, lead architecture reviews, and take point on technical response to major incidents.
Education & Experience
Technical Skills
Our Commitment: Personify Health is an equal opportunity employer committed to diversity, equity, inclusion, and belonging. We cultivate a work environment where differences are celebrated, and employees of all backgrounds are empowered to thrive—because diversity is core to who we are and critical to our work in health and wellbeing.
Stay Safe: Personify Health will never ask for payment or sensitive personal information like social security numbers during hiring. All official communication comes from verified company email addresses and or our secure applicant tracking system. Suspicious requests? Report them to talent@personifyhealth.com. View all legitimate openings at personifyhealth.com/careers.
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