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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and maintaining scalable ETL/ELT pipelines using Python and SQL, while ensuring data quality and compliance with federal regulations. Proficient in cloud data solutions and data modeling, with a strong focus on integrating diverse data sources and optimizing workflows.
Highest-signal resume keywords
ETL/ELT Pipeline DevelopmentPython ProgrammingSQL ProficiencyApache Spark/PySpark ExperienceCloud Data Solutions (AWS/Azure)
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringData IntegrationData ModelingDatabase OptimizationData Quality ChecksAutomated TestingVersion Control (Git)CI/CD PracticesData WarehousingData Transformation
Tools & Technologies
Power BIApache AirflowREST APIsJSONCloud Data Services
Certifications & Qualifications
Cloud CertificationsData Engineering Certifications
Industry Keywords
VA ComplianceFISMAPIIPHIAgileDevSecOps
Tech Stack
Tools & technologiesAirflowApacheAWSAzureCloudETLPostgresPySparkPythonSparkSQL
About the role
Key responsibilities & impact- Design, develop, and maintain scalable, secure ETL/ELT pipelines using Python, SQL, PySpark, and modern data engineering frameworks
- Integrate structured, semi-structured, and unstructured data from VA systems, claims applications, evidence repositories, medical records, external sources, and enterprise databases
- Engineer solutions for claims intake, evidence collection, validation, workflow routing, status tracking, and downstream processing
- Develop and optimize cloud data solutions using AWS, Azure, or comparable environments
- Design and maintain relational, dimensional, and analytical data models using data lake, warehouse, and lakehouse patterns
- Process large-scale datasets with Apache Spark and PySpark; optimize queries, databases, transformations, and workflows
- Establish data validation, reconciliation, monitoring, quality controls, metadata, lineage, traceability, and documented business rules
- Build batch, incremental, and event-driven workflows with testing, scheduling, error handling, logging, and monitoring
- Develop analysis-ready datasets and data products for Power BI, operational analytics, predictive analytics, and approved AI/ML workflows
- Implement encryption, role-based access controls, auditability, data minimization, and compliance with VA, FISMA, privacy, records-management, PII, and PHI requirements
- Apply Git version control, code reviews, CI/CD, automated testing, documentation, and infrastructure as code
- Collaborate with VA stakeholders, claims subject matter experts, architects, developers, and analytics teams
- Modernize legacy integrations and improve interoperability, performance, data reliability, and claims workflow efficiency
Requirements
What you’ll need- Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical discipline, or equivalent relevant professional experience
- 5+ years of experience in data engineering, software engineering, enterprise data integration, or development of production data systems
- Strong hands-on proficiency in Python and SQL, including complex queries, data transformations, automation scripts, and production data pipelines
- Experience designing, developing, and maintaining scalable ETL/ELT pipelines involving multiple enterprise data sources and complex data transformations
- Experience with Apache Spark, PySpark, or comparable distributed data-processing technologies
- Hands-on experience with cloud data services in AWS, Azure, or comparable cloud environments
- Strong understanding of relational databases, data modeling, data warehousing, and database optimization, including SQL Server, PostgreSQL, or comparable technologies
- Experience integrating data through REST APIs, JSON, secure file exchanges, and other enterprise integration methods
- Experience implementing data-quality checks, pipeline monitoring, automated testing, version control, and CI/CD or comparable practices
- Familiarity with secure data handling, access controls, and governance principles for sensitive enterprise or federal information
- Ability to satisfy VA personnel suitability, applicable Public Trust requirements, and federal security and privacy requirements
- Desired: VA/Veterans Benefits experience; VBMS, VA Lighthouse APIs, or comparable systems; modern cloud data platforms; Apache Airflow and event-driven integration; Power BI or Microsoft Power Platform; AI/ML, OCR, NLP, or document processing; legacy modernization; Agile or DevSecOps federal delivery
- Relevant cloud, data engineering, or platform certifications are a plus