Senior AI-Driven Data Engineer & Product Owner

Perform; Nashville (TN); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Perform is seeking a Senior Forward Deployed Data Engineer to own the data platform and partner with business stakeholders. You will build and operate Azure Databricks pipelines, integrate Salesforce, SQL Server, Snowflake, and a new payments platform, and deliver AI-ready data products end to end.

You will use Claude Code and other AI tools to accelerate discovery, validation, and production deployment while ensuring data quality and governance in a regulated healthcare context.

Qualifications

• BS in Computer Science, Data Science, or a related field.
• 6+ years in data engineering or a hybrid data engineering and analytics role.
• Deep hands-on experience with Azure Databricks, including notebooks, Delta Lake, Unity Catalog, and production-scale pipelines.
• Strong Python and SQL, with experience in PySpark and distributed data processing.
• Experience building and operating pipelines that serve analytics, ML models, and operational systems, not only batch ETL jobs.
• Direct experience working with business stakeholders to define requirements, shape data products, and deliver measurable outcomes.
• Active, daily use of AI coding tools as a force multiplier, with Claude Code as the primary platform and familiarity across other leading models.
• Data architecture experience, including designing systems rather than only implementing against someone else's design.
• Experience building data products for marketing or growth teams, such as customer segmentation, campaign attribution, or engagement and retention analytics.
• Strong communication skills and a track record of presenting technical work to non-technical audiences.
• Proven ability to take an ambiguous business problem and turn it into a working data solution with minimal direction.

Responsibilities

• Design, build, and operate the data platform on Azure Databricks, covering ingestion, transformation, storage, and serving layers that power analytics, AI models, and operational reporting.
• Build and maintain pipelines across the business ecosystem, including Salesforce, SQL Server, Snowflake, third-party sources, and a new cloud-native payments platform.
• Engineer for quality and trust through validation checks, anomaly detection, lineage tracking, and documentation that every downstream consumer can rely on.
• Write clean, version-controlled, production-grade code. Think like a software engineer building a product, not a script runner maintaining jobs.
• Own architecture decisions across storage, transformation, orchestration, and serving, balancing delivery speed against long-term maintainability.
• Partner directly with stakeholders across physician growth, member services, finance, and operations to understand how data drives decisions, then build for those decisions rather than for abstract requirements.
• Act as technical product owner for your domain areas. Own the backlog, prioritize by business impact, and ship iteratively without waiting for a PM to sequence your work.
• Translate ambiguous business questions into data models, feature tables, and curated datasets that analysts and data scientists can build on immediately.
• Push back on vague requirements until they are sharp enough to build against.
• Close the loop. Follow your data through to the dashboard, the model, or the operational workflow and validate that it is actually driving the outcome.
• Communicate tradeoffs, limitations, and timelines clearly to technical and non-technical audiences alike.
• Use Claude Code and agentic development as your primary workflow, including AI-driven pipeline generation, automated testing, and rapid prototyping, to ship at a pace traditional approaches cannot match.
• Build data infrastructure that is AI-ready: well-documented, semantically clear, and structured so that AI tools and agents can reason over it effectively.
• Support data workflows behind AI and LLM applications, including curated context, retrieval-ready datasets, and the evaluation data needed to measure whether those systems are working.
• Scout, evaluate, and adopt emerging AI tools and platforms that make the data team faster, separating real value from hype through hands-on testing.
• Share what you learn. Document patterns, run demos, and help the broader team adopt AI-first workflows with confidence.
• Apply appropriate handling, access control, and compliance practices for sensitive and regulated healthcare data.

Skills

Azure Databricks

Python

SQL

PySpark

AI coding tools

Data architecture

Data products

Communication

Education

BS in Computer Science, Data Science, or related field

Tools

Unity Catalog

Delta Lake

Claude Code

Salesforce

Snowflake

Job description

Perform is seeking a Senior Forward Deployed Data Engineer to own the data platform and partner with business stakeholders. You will build and operate Azure Databricks pipelines, integrate Salesforce, SQL Server, Snowflake, and a new payments platform, and deliver AI-ready data products end to end.

You will use Claude Code and other AI tools to accelerate discovery, validation, and production deployment while ensuring data quality and governance in a regulated healthcare context.