Senior Data Engineer

Analytica is seeking a Senior Data Engineer to support large-scale healthcare data modernization and analytics initiatives. This role is responsible for designing, building, optimizing, and operating enterprise-grade data platforms and pipelines that support mission-critical healthcare programs. The ideal candidate possesses deep expertise in cloud-native data engineering, Data Ops practices, and regulated healthcare environments.

The Senior Data Engineer will lead the development and maintenance of scalable, secure, and auditable data pipelines while ensuring data quality, reliability, and compliance with federal healthcare regulations and CMS data governance requirements. This individual will serve as a technical leader, collaborating with data architects, data scientists, business analysts, and program stakeholders to deliver high‑quality data products and operational capabilities.

Analytica offers competitive compensation with opportunities for bonuses, employer‑paid health care, training and development funds, and 401(k) match.

• Design, develop, and maintain scalable batch and streaming data pipelines using Databricks and/or cloud‑native services.
• Build and optimize ETL/ELT workflows that support operational reporting, analytics, machine learning, and data‑sharing initiatives.
• Develop and maintain medallion architecture patterns (Bronze, Silver, Gold) within Databricks Lakehouse environments.
• Implement data integration solutions across multiple structured and unstructured healthcare data sources.
• Design reusable frameworks, templates, and accelerators that improve engineering productivity and consistency.

• Establish and maintain Data Ops processes that support reliable, automated, and observable data pipelines.
• Monitor pipeline health, performance, data quality, and operational SLAs.
• Implement automated testing, deployment, version control, and CI/CD practices for data products.
• Develop proactive monitoring, alerting, and incident response procedures.
• Troubleshoot and resolve production data issues while minimizing operational impact.

• Ensure solutions comply with CMS, federal, and healthcare‑specific security, privacy, and data governance requirements.
• Support environments containing protected health information (PHI), personally identifiable information (PII), and other sensitive healthcare datasets.
• Implement auditability, lineage, metadata management, and data quality controls.
• Partner with governance and security teams to ensure compliance with applicable standards and policies.

• Collaborate with solution architects and customer stakeholders to define data platform strategy and implementation roadmaps.
• Lead technical design reviews and contribute to enterprise data architecture decisions.
• Optimize data storage, processing performance, and cost management within cloud environments.
• Mentor junior engineers and promote engineering best practices across teams.

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related technical discipline.
• 8+ years of data engineering experience, including large‑scale enterprise data environments.
• 3+ years supporting CMS or other federal healthcare programs.
• Experience operating and supporting production‑grade data platforms in regulated environments.
• Demonstrated experience with Data Ops and modern data engineering practices.

• Expert‑level experience with Databricks Lakehouse Platform.
• Strong proficiency with Apache Spark, PySpark, SQL, and Python.
• Experience designing and maintaining operational data pipelines at enterprise scale.
• Hands‑on experience with cloud data platforms in AWS or Azure cloud environments.
• Experience implementing CI/CD pipelines using Git‑based development workflows.
• Expertise in data quality, observability, lineage, metadata management, and monitoring frameworks.
• Experience with orchestration and workflow management tools.
• Strong knowledge of lakehouse, warehouse, and modern data architecture patterns.

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