Senior Data Engineer
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Job Description
Senior Data Engineer II responsible for building advanced data solutions at Advarra. Collaborating with teams to enable analytics and AI-driven decision-making in clinical research.
Responsibilities:
- Design & Build Data Systems: Architect and implement scalable data pipelines, lakehouse/lake/warehouse environments, APIs, and orchestration workflows to support analytics, AI/ML, and business intelligence.
- Enable AI & ML at Scale: Partner with Data Science and AI teams to productionize ML models, automate workflows, and enable AI orchestration frameworks (e.g., MLflow, Airflow, Databricks workflows).
- Technical Leadership: Act as a hands-on subject matter expert in Databricks, Python, Spark, and related technologies—driving adoption of best practices and mentoring other engineers.
- Optimize Performance: Ensure data pipelines and platforms are highly available, observable, and performant at scale through monitoring, automation, and continuous improvement.
- Ensure Compliance & Security: Build solutions that adhere to data governance, privacy, and regulatory frameworks (HIPAA, SOC 2, GCP, GDPR) within clinical research, life sciences, and healthcare contexts.
- Collaborate Across Functions: Work closely with platform engineering, analytics, product management, and compliance teams to deliver aligned solutions that meet enterprise needs.
- Advance Modern Architectures: Contribute to evolving data platform strategies, including event-driven architectures, data mesh concepts, and lakehouse adoption.
Requirements:
- Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent practical experience.
- 8+ years of data engineering experience in designing, implementing, and optimizing large-scale data systems.
- Strong proficiency in Python, with production-level experience in building reusable, scalable data pipelines.
- Hands-on expertise with Databricks (Delta Lake, Spark, MLflow), and modern orchestration frameworks (Airflow, Prefect, Dagster, etc.).
- Proven track record of deploying and supporting AI/ML pipelines in production environments.
- Experience with cloud platforms (AWS, Azure, or GCP) for building secure and scalable data solutions.
- Familiarity with regulatory compliance and data governance standards in healthcare or life sciences.
Benefits:
- health coverage
- paid holidays
- variable bonus
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