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Analytica

Public-sector data-driven consulting and technology services

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeWashington, DC, USAIn-person

About the Job

Requirements

  • A 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 and supporting production-grade data platforms in regulated environments.
  • Demonstrated experience with DataOps and modern data engineering practices.
  • Expert-level experience with the 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.
  • 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.
  • Experience supporting CMS, Medicare, Medicaid, or other federal healthcare data programs.
  • Understanding of healthcare data governance, security, privacy, and compliance requirements.
  • Experience working with healthcare data standards and regulated datasets.
  • Familiarity with Federal Information Security requirements and operational controls.
  • Strong problem-solving and troubleshooting abilities.
  • Ability to translate business requirements into scalable technical solutions.
  • Ability to operate effectively in highly regulated healthcare environments.

Responsibilities

  • 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 DataOps 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.

Desired Qualifications

  • Databricks Certified Data Engineer Professional certification.
  • Additional Databricks certifications.
  • Experience supporting cloud-native analytics platforms for CMS.
  • Experience implementing Delta Lake, Unity Catalog, and advanced Databricks governance capabilities.
  • Familiarity with machine learning operations (MLOps) and AI/ML data pipelines.
  • Experience with Collibra, Informatica, Unity Catalog, or comparable data governance platforms.
  • Experience supporting FedRAMP- or FISMA-compliant environments.
  • Prior experience leading technical teams or serving as a technical lead.

About the Company

Analytica

Public-sector data-driven consulting and technology services

Analytica provides data-driven consulting and technology services to U.S. public-sector agencies in health, civilian, and national security. Its offerings combine data analytics, systems integration, and technology implementation to help government entities modernize operations and improve decision-making. The company differentiates itself through a strong track record with public-sector modernization recognized by organizations like NYU’s Governance Lab, its SBA 8(a) and HUBZone certifications, and being named among Inc.’s fastest-growing U.S. companies for three consecutive years. Analytica’s goal is to enable government clients to use data and technology to deliver better services, increase efficiency, and strengthen national security.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Washington DC, District of Columbia
Founded
2007

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