• Build and nurture the team Recruit, mentor, and grow a team of data and analytics engineers, cultivating a culture focused on data quality, accountability, and continuous learning; guide personal development and ongoing professional growth.
• Drive delivery and technical strategy Closely partner with Product leadership to translate clinical and business priorities into a clear, actionable technical roadmap; oversee sprint capacity planning and manage a transparent process for balancing strategic projects with urgent requests.
• Architect and optimize data pipelines Design efficient batch and real-time ELT workflows to process structured (FHIR/EHR, claims) and unstructured (NLP/LLM-generated) data, leveraging Snowflake, dbt, Python, Spark, Iceberg, and state-of-the-art NLP/GenAI solutions.
• Enhance the data model Lead dimensional modeling, establish robust data contracts, and maintain comprehensive documentation to ensure reliability and scalability of analytics as the business grows.
• Promote quality with SDET collaboration Partner with our Software Development Engineering in Test (SDET) team to automate data validation, implement regression tests, and enforce rigorous quality standards.
• Ensure compliance and governance Set standards for data lineage, masking, security, and access controls to comply with HIPAA and SOC 2; institute automated quality monitoring and anomaly detection.
• Oversee advanced NLP and GenAI initiatives Manage sophisticated NLP-driven abstraction, summarization, and enrichment pipelines; establish quality benchmarks, support skill development, and lead vendor selection (data annotation, model evaluation, prompt engineering) ensuring compliance with clinical and regulatory standards.
• Resolve complex technical issues Provide hands-on troubleshooting for SQL query performance, dbt model optimizations, Spark job failures, and pipeline disruptions.
• Cross-team collaboration Actively engage with Product, Clinical, Customer Success, and Application Engineering teams, ensuring alignment on dependencies and clearly communicating the strategic value of data engineering deliverables.
• Implement advanced DataOps and DevOps practices Champion best practices for CI/CD, infrastructure as code (IaC, OpenTofu), automated testing, observability, and cost optimization (especially around Snowflake/dbt), in collaboration with DevOps and technical leaders.

• 8+ years experience in data engineering or analytics engineering, with at least 3 years managing technical teams.
• Expert proficiency in SQL and substantial hands-on experience with Snowflake or similar cloud data warehouses.
• Production-level experience with dbt (Core or Cloud), including incremental builds, comprehensive testing, and CI/CD automation.
• Strong Python skills for data processing, orchestration, and pipeline scripting.
• Practical experience using Spark (PySpark or Scala) and understanding distributed processing architectures.
• Familiarity with modern CI/CD and infrastructure-as-code practices; ability to effectively partner with DevOps/SRE teams.
• Proven track record delivering data products within regulated or high-stakes environments (healthcare, fintech, etc.).
• Exceptional communication, leadership, and project management skills to drive cross-functional alignment and accountability.
• Experience with modern data lake technologies (Apache Iceberg, Delta Lake, Hudi) and file formats (Parquet, ORC).
• Knowledge of streaming data frameworks (Kafka, Kinesis, Pulsar) and event-driven architecture.
• Understanding healthcare data standards (FHIR, HL7, EHR, claims, genomics) and regulatory compliance (HIPAA).
• Familiarity with orchestration platforms (Temporal, Airflow, Prefect) and monitoring tools (Datadog, Prometheus/Grafana).
• Previous involvement in ML/AI or NLP pipelines, especially within clinical or healthcare contexts.
• Experience managing multi-cloud or hybrid infrastructures (AWS, Azure, Alibaba Cloud).

Why Join OncoLens?

• Mission Directly contribute to improving patient outcomes through innovative oncology care solutions.
• Autonomy and leadership Fully shape and influence the strategic direction of data engineering with strong executive support.
• Cutting-edge technology stack Work with Snowflake, dbt, Spark, Python, Iceberg, AWS, Temporal, OpenTofu, Spacelift, and Kafka.
• Accelerated career growth Play a key role in shaping processes, architecture, and culture in a high-growth environment.
• Remote-first culture Enjoy flexible working conditions, competitive compensation, equity, top-tier benefits, and generous PTO.

Ready to architect the data platform driving transformative oncology care? email keithanderson@oncolens.com