Analytica

1 week ago

Senior Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Design, build, optimize, and operate enterprise-grade batch and streaming data pipelines that modernize healthcare data and support mission-critical analytics. Lead scalable, secure, auditable lakehouse solutions using Databricks, including ETL/ELT workflows and medallion (Bronze/Silver/Gold) patterns. Establish DataOps practices—monitoring, testing, CI/CD, and incident response—while ensuring CMS and regulated healthcare compliance and data quality, reliability, and observability.

Location: Washington

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Design and maintain scalable batch and streaming data pipelines using Databricks and/or cloud-native services.
•Build and optimize ETL/ELT workflows supporting operational reporting, analytics, machine learning, and data-sharing initiatives.
•Establish DataOps processes for reliable, automated, observable pipelines, including monitoring, alerting, testing, and CI/CD.
•Ensure compliance with CMS, federal healthcare security/privacy/data governance requirements, including auditability, lineage, metadata management, and quality controls.
•Lead technical design reviews, contribute to enterprise data architecture decisions, and mentor junior engineers while resolving production data issues.

Pay and Benefits

Perks:Health Insurance401kLearning Budget

Key Requirements

•8+ years of data engineering experience in large-scale enterprise data environments, including production-grade regulated systems.
•3+ years supporting CMS or other federal healthcare programs and working knowledge of healthcare data governance, security, privacy, and compliance.
•Expert-level experience with the Databricks Lakehouse Platform and building/maintaining operational data pipelines at enterprise scale.
•Strong proficiency with Apache Spark, PySpark, SQL, and Python, including ETL/ELT and data integration across structured and unstructured sources.
•Demonstrated DataOps experience, including automated testing, deployment, version control, CI/CD, observability, lineage, metadata management, and monitoring frameworks.

Experience:8+ yearsHealthcareFederal contractingRegulated dataData engineeringDataOps

Education:Bachelor's

Skills:Problem-solvingTroubleshootingWritten communicationVerbal communicationMentorship

Certifications:Databricks Certified Data Engineer Professional

Tech Stack:DatabricksApache SparkPySparkSQLPythonAWSAzureETLELTLakehouseCI/CDGitDelta LakeUnity CatalogCollibraInformatica

Company Brief

Analytica

Analytica is a federal-focused consulting and technology services firm delivering data, analytics, AI, and IT modernization solutions to health, civilian, and national security agencies in the U.S.

Industry: Consulting

Company Size: Medium (51 to 250 employees)

Revenue: USD 25M to 50M

Growth: Established Company

Headquarters: Washington, United States

Founded: 2009

Glassdoor: 3.4

Website LinkedIn Glassdoor

Loading job details...

Preparing the role view and application actions.

Analytica

1 week ago

Senior Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: Washington

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Design and maintain scalable batch and streaming data pipelines using Databricks and/or cloud-native services.
•Build and optimize ETL/ELT workflows supporting operational reporting, analytics, machine learning, and data-sharing initiatives.
•Establish DataOps processes for reliable, automated, observable pipelines, including monitoring, alerting, testing, and CI/CD.
•Ensure compliance with CMS, federal healthcare security/privacy/data governance requirements, including auditability, lineage, metadata management, and quality controls.
•Lead technical design reviews, contribute to enterprise data architecture decisions, and mentor junior engineers while resolving production data issues.

Pay and Benefits

Perks:Health Insurance401kLearning Budget

Key Requirements

•8+ years of data engineering experience in large-scale enterprise data environments, including production-grade regulated systems.
•3+ years supporting CMS or other federal healthcare programs and working knowledge of healthcare data governance, security, privacy, and compliance.
•Expert-level experience with the Databricks Lakehouse Platform and building/maintaining operational data pipelines at enterprise scale.
•Strong proficiency with Apache Spark, PySpark, SQL, and Python, including ETL/ELT and data integration across structured and unstructured sources.
•Demonstrated DataOps experience, including automated testing, deployment, version control, CI/CD, observability, lineage, metadata management, and monitoring frameworks.

Experience:8+ yearsHealthcareFederal contractingRegulated dataData engineeringDataOps

Education:Bachelor's

Skills:Problem-solvingTroubleshootingWritten communicationVerbal communicationMentorship

Certifications:Databricks Certified Data Engineer Professional

Tech Stack:DatabricksApache SparkPySparkSQLPythonAWSAzureETLELTLakehouseCI/CDGitDelta LakeUnity CatalogCollibraInformatica

Company Brief

Analytica

Analytica is a federal-focused consulting and technology services firm delivering data, analytics, AI, and IT modernization solutions to health, civilian, and national security agencies in the U.S.

Industry: Consulting

Company Size: Medium (51 to 250 employees)

Revenue: USD 25M to 50M

Growth: Established Company

Headquarters: Washington, United States

Founded: 2009

Glassdoor: 3.4

Website LinkedIn Glassdoor