Cleared Data Engineer
Accenture Federal Services
Washington, DC4d agovia LinkedIn
Key Responsibilities
- Design, build, and maintain scalable end-to-end data pipelines using Databricks, Spark, and related technologies.
- Develop efficient data processing and transformation workflows to support analytics and reporting needs.
- Integrate diverse data sources including APIs, databases, and cloud storage into unified datasets.
- Work closely with cross-functional teams (data science, analytics, business units) to design and implement data solutions that align with business goals.
- Implement robust validation, monitoring, and observability processes to ensure data accuracy, completeness, and reliability.
- Contribute to data governance, security, and automation initiatives within the data ecosystem.
- Leverage AWS services (e.g., S3, Glue, Lambda, Redshift) to build and deploy data solutions in a cloud-native environment.
Requirements & Tech Stack
- Experience with cloud-based ETL services (e.g. AWS Glue, Google Cloud Dataflow, Azure Data Factory)
- Experience with cloud data warehousing technologies (e.g. Amazon Redshift, Google BigQuery, Snowflake)
- Experience with Python, SQL, Spark, and PySpark
- Experience with data platforms like Databricks, Palantir, and Snowflake
- Familiarity with data orchestration and data quality processes
Bonus Points
- Experience working with federal clients
- Experience with Docker/Kubernetes
- Experience with Hadoop/Spark
- Experience with NiFi
- Experience with ELK stack
- Experience with Agile / Scrum
- Experience with COTS and open-source data engineering tools such as ElasticSearch and NiFi
- Data engineering certification such as Palantir Foundry Data Engineer, Azure Data Engineer Associate, Google Professional Data Engineer, IBM Certified Data Engineer, or similar
Security Clearance
- Active Top Secret or TS/SCI or TS/SCI with polygraph clearance