Junior Data Engineer | Jobs at Falcon IT and Staffing Solutions

_{27th February, 2026}

Embark on an exciting journey as a Junior Data Engineer with the Department of Transportation in Washington, D.C.

In this permanent, full-time role, you'll have the opportunity to earn a competitive salary ranging from $70,000 to $90,000 while playing a crucial part in modernizing the agency's legacy Informatica-based ETL pipelines.

Join a dynamic team of senior engineers, data architects, and QA professionals as you dive into the world of Databricks, PySpark, and Spark SQL, driving data migration and modernization efforts within a data-heavy, potentially regulated environment.

Modernize Legacy ETL Pipelines - Leverage your expertise in Informatica PowerCenter to analyze workflows and mappings, then convert them into Databricks pipelines using PySpark and Spark SQL.
Implement Cutting-Edge Data Architectures - Spearhead the implementation of the medallion architecture (landing → bronze → silver) for data ingestion from on-prem and cloud sources into Databricks.
Collaborate with Cross-Functional Teams - Work closely with senior engineers, data architects, and QA teams throughout iterative migration cycles, ensuring seamless data migration and modernization.

Requirements:

Analyze Informatica workflows and mappings to understand source-to-target logic, transformations, dependencies, and scheduling order.
Convert Informatica mappings into Databricks pipelines using PySpark and Spark SQL.
Implement data ingestion from on-prem and cloud sources into Databricks using the medallion architecture (landing → bronze → silver).
Adapt existing ETL logic to align with a new enterprise data model, identifying gaps and required transformation changes.
Support unit testing, reconciliation, and data validation between legacy and modern pipelines.

Preferred Qualifications:

2-3 years of experience in data engineering, ETL development, or data integration.
Working knowledge of Informatica PowerCenter, including: Mappings, workflows, and sessions. Common transformations (Source Qualifier, Expression, Lookup, Joiner, Aggregator, Router, Filter).
Basic to intermediate experience with Databricks, including: PySpark, Spark SQL, Notebooks, and jobs.
Strong SQL fundamentals, including joins, aggregations, and window functions.
Solid understanding of ETL / ELT concepts, data warehousing principles, and batch processing.
Strong attention to detail and analytical skills.
Ability to clearly document technical logic and communicate findings to technical team members.
Data Modeling and Analysis Skills:
Interpret legacy data models and mapping documentation.
Identify how legacy fields map (or do not map) to a new target data model.
Flag missing logic, derived fields, or transformation gaps early in the migration process.
Perform detailed data validation, including reconciliation of row counts and aggregates.
Prior experience in regulated or data-heavy environments (finance, government, healthcare) is preferred.
Exposure to Informatica-to-Databricks migrations or similar data modernization efforts is preferred.
Familiarity with Delta Lake and medallion architecture (Bronze / Silver / Gold) is preferred.
Basic understanding of AWS, including S3 and IAM concepts.
Experience reading or generating code from Informatica XML exports.
Bachelor's Degree in Computer Science, Engineering, or a related field (or equivalent experience).
Experience supporting report rationalization and data migration initiatives.
Clearance: US Citizen eligible to obtain DOT Public Trust.

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