Senior Data Engineer (Azure Data Factory Databricks, PostgreSQL, Python) -(USC or GC only) - Local candidates only

Senior Data EngineerLocation: Reston VA (on-site 9-10 days a month) - Only local candidates will be considered. No relocation is available. Salary: Open and will be commensurate with experience. This is a full time position and this person must be a Green Card Holder or be a US Citizen of the United States, as per the company, due to government compliance.Must have the following: Azure Data Factory, Databricks, Python, SQL, ETL/ELT pipelines, Data Lake, Spark, Data Engineering, Cloud Data Platforms, CI/CDThe Data Engineer will serve as the company's subject matter expert on a multitude of data engineering methods, data integration and data management technologies. This is a highly technical role responsible for leading the data engineering lifecycle across the organization's data planes — from raw data ingestion through data cleansing, data standardization, data transformation, data modeling, and data delivery. The scope of the role spans data integration with on-premises source systems through cloud-based data processing, data storing, and works in tandem with other teams who support data serving and data delivery layers. Responsibilities:Design, build, and maintain scalable production data pipelines supporting enterprise data platformsPerform exploratory data analysis, statistical analysis, and data validation to support analytics and reportingDevelop and optimize ETL/ELT workflows including job design, orchestration, and performance tuningBuild and maintain relational database schemas, queries, and stored proceduresWork within Azure-based data environments including Data Factory, Databricks, and Data Lake StorageCollaborate with analytics, BI, and engineering teams to deliver reliable data productsImplement monitoring, logging, and observability for data pipelinesMaintain documentation, data lineage, and governance standardsParticipate in architecture discussions and contribute to long-term data platform strategyRequirements:Bachelor's degree in Computer Science, Statistics, Mathematics, Information Science, Data Engineering, Finance, or related field (Master's preferred)5 years of data engineering experience working with production data pipelines5 years of applied data analysis and statistical data work3 years of ETL / ELT development experience3 years working with relational databases and performance tuningExperience with Azure data services (Data Factory, Databricks, Data Lake, Synapse, Delta Lake, or similar)Strong programming experience with Python, PySpark, SQL, and BashExperience with Kafka, SAP data services, or similar integration tools preferredExperience with PostgreSQL, SAP ASE, or comparable databasesExperience with Power BI or BusinessObjects is a plusExperience with CI/CD pipelines, Git, Kubernetes, and infrastructure-as-codeKnowledge of data governance, cataloging, and access controlExperience with monitoring tools such as Datadog, Grafana, or PrometheusAbility to work independently while managing multiple prioritiesStrong communication and documentation skillsMust be eligible to work in the United States