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Depends on experience
AWS Glue,Azure Data Factory,Cassandra,Delta Lake,DynamoDB,MongoDB,Oracle,PostgreSQL,Power BI,PySpark,Python,S3/ADLS,Spark SQL,SQL,SQL Server,Tableau
Work type: Hybrid - 3 days On site and two days remote
Work authorization: US local resources,Work authorization required,Work authorization sponsored,Work authorization in field of study
Veteran Service: Yes
Number of hirings: 1
Job Details
Senior Data Engineer
Exp: 10+ Years Minimum
Client: Federal Agency
Location: Washington, DC Metro Area — Hybrid (3 days remote / 2 days on-site)
NOTE : Must be based in, or willing to relocate to, the Washington, DC metro area, with availability for on-site work
Employment Type: C2C
Eligibility: USC - U.S. Citizenship required - Must able to get Public Trust Clearance
Public Trust clearance is plus.
hands-on with Python for data engineering, scripting, or analysis
hands-on with Apache Spark (PySpark or Spark SQL) at scale
Strong SQL and experience across relational and/or distributed data systems
Data modeling chops — dimensional/star schema, normalization, ER design
Comfort across a mix of database technologies (e.g., PostgreSQL, SQL Server, Oracle, MongoDB, Cassandra, DynamoDB)
A track record of building visualizations that make data's implications clear to a non-technical audience
Hands-on Databricks experience in Azure, AWS, or GCP
Cloud-native data services (Azure Data Factory, AWS Glue, S3/ADLS, Delta Lake)
BI/visualization tools like Power BI or Tableau
Exp: 10+ Years Minimum
Client: Federal Agency
Location: Washington, DC Metro Area — Hybrid (3 days remote / 2 days on-site)
NOTE : Must be based in, or willing to relocate to, the Washington, DC metro area, with availability for on-site work
Employment Type: C2C
Eligibility: USC - U.S. Citizenship required - Must able to get Public Trust Clearance
Public Trust clearance is plus.
hands-on with Python for data engineering, scripting, or analysis
hands-on with Apache Spark (PySpark or Spark SQL) at scale
Strong SQL and experience across relational and/or distributed data systems
Data modeling chops — dimensional/star schema, normalization, ER design
Comfort across a mix of database technologies (e.g., PostgreSQL, SQL Server, Oracle, MongoDB, Cassandra, DynamoDB)
A track record of building visualizations that make data's implications clear to a non-technical audience
Hands-on Databricks experience in Azure, AWS, or GCP
Cloud-native data services (Azure Data Factory, AWS Glue, S3/ADLS, Delta Lake)
BI/visualization tools like Power BI or Tableau
Interview type: Telephonic
Experience years required: 0