Senior Data Engineer (PostgreSQL, Python, Azure)
Location : 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.
NOTE: 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/CD
The 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 platforms
- Perform exploratory data analysis, statistical analysis, and data validation to support analytics and reporting
- Develop and optimize ETL/ELT workflows including job design, orchestration, and performance tuning
- Build and maintain relational database schemas, queries, and stored procedures
- Work within Azure-based data environments including Data Factory, Databricks, and Data Lake Storage
- Collaborate with analytics, BI, and engineering teams to deliver reliable data products
- Implement monitoring, logging, and observability for data pipelines
- Maintain documentation, data lineage, and governance standards
- Participate in architecture discussions and contribute to long-term data platform strategy
Requirements:
- 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 pipelines
- 5 years of applied data analysis and statistical data work
- 3 years of ETL / ELT development experience
- 3 years working with relational databases and performance tuning
- Experience with Azure data services (Data Factory, Databricks, Data Lake, Synapse, Delta Lake, or similar)
- Strong programming experience with Python, PySpark, SQL, and Bash
- Experience with Kafka, SAP data services, or similar integration tools preferred
- Experience with PostgreSQL, SAP ASE, or comparable databases
- Experience with Power BI or BusinessObjects is a plus
- Experience with CI/CD pipelines, Git, Kubernetes, and infrastructure-as-code
- Knowledge of data governance, cataloging, and access control
- Experience with monitoring tools such as Datadog, Grafana, or Prometheus
- Ability to work independently while managing multiple priorities
- Strong communication and documentation skills
- Must be eligible to work in the United States
INDH
Senior Data Engineer, Azure Data Factory, Databricks, Python, SQL, ETL, ELT, Data Pipelines, Data Lake, Spark, Delta Lake, Azure Synapse, Cloud Data Platform, Data Engineering, Big Data, Kafka, PostgreSQL, SAP Data Services, Power BI, CI/CD, Kubernetes, Data Governance, Data Lineage, Analytics Engineering, Data Integration, Financial Data, Enterprise Data, Data Architecture, BI Reporting, PySpark, Bash, Cloud Engineering, Data Warehouse, Data Modeling, Observability, Grafana, Prometheus, Datadog, Azure Cloud, Data Platform Engineer, Statistical Analysis