4 months ago
Washington, DC, USASenior
Responsibilities
- Design, develop, maintain, and optimize scalable batch and streaming data pipelines using Databricks and cloud-native services.
- Build ETL/ELT workflows and Databricks Lakehouse medallion architectures across structured and unstructured healthcare data sources.
- Create reusable data engineering frameworks, templates, and accelerators.
- Establish DataOps processes for pipeline automation, observability, monitoring, data quality, deployment, and operational SLAs.
- Implement automated testing, Git-based version control, CI/CD, alerting, incident response, and production troubleshooting.
- Ensure data platforms support auditability, lineage, metadata management, privacy, security, and healthcare regulatory compliance.
- Collaborate on data platform strategy, implementation roadmaps, technical design reviews, and enterprise architecture decisions.
- Optimize cloud data storage, processing performance, and costs.
- Mentor junior engineers and promote engineering best practices across teams.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical discipline.
- At least 8 years of data engineering experience, including large-scale enterprise data environments.
- At least 3 years supporting CMS or other federal healthcare programs.
- Experience operating production-grade data platforms in regulated environments.
- Expert-level Databricks Lakehouse experience and strong proficiency with Apache Spark, PySpark, SQL, and Python.
- Experience with AWS or Azure cloud data platforms and enterprise-scale operational data pipelines.
- Experience implementing CI/CD pipelines using Git-based development workflows.
- Expertise in data quality, observability, lineage, metadata management, monitoring frameworks, orchestration, and workflow management.
- Strong knowledge of lakehouse, warehouse, and modern data architecture patterns.
- Understanding of CMS, Medicare, Medicaid, healthcare data governance, security, privacy, compliance requirements, and regulated healthcare datasets.
- Familiarity with Federal Information Security requirements and operational controls.
- Preferred qualifications include Databricks Certified Data Engineer Professional or other Databricks certifications, Delta Lake, Unity Catalog, MLOps, AI/ML data pipelines, Collibra, Informatica, FedRAMP or FISMA environments, and technical team leadership.
- Strong problem-solving, troubleshooting, communication, business translation, and operational excellence capabilities.
Benefits
- Competitive compensation with opportunities for bonuses.
- Employer-paid health care.
- Training and development funds.
- 401(k) match.
About Analytica
Analytica provides data and software engineering, analytics, and IT modernization consulting to U.S. government health, civilian, and national security agencies. Its services span cloud and enterprise data platforms (e.g., AWS, Databricks), DevSecOps, GIS, and AI/ML, delivered via government contracts. Founded in 2009 and headquartered in Washington, DC, the privately held firm is an SBA-certified 8(a) and HUBZone small business.