Data Engineer

Unissant•Washington, VA

8d•Onsite

About The Position

Unissant, Inc. is seeking a Data Engineer to join their team in Washington, DC, in support of the Department of Homeland Security (DHS), Immigration and Customs Enforcement (ICE), Law Enforcement Systems and Analysis (LESA) program within the Statistical Tracking Unit (STU). The STU is ICE's official statistical reporting unit, responsible for accountability, consistency, and accuracy in reporting ICE operations. The STU maintains critical reports and queries, supports data requests from Congress and interagency bodies, handles FOIA responses, litigation needs, and drives continuous reporting improvements through the ICE Integrated Decision Support System (IIDS) and ENFORCE. The ideal candidate will possess strong technical expertise in data pipeline development, batch and streaming architecture, data modeling, and cloud data platforms to establish the infrastructure foundation necessary for STU analysts and data scientists to deliver accurate and timely statistical reporting.

Requirements

3–10 years of experience in data engineering, data architecture, or a closely related discipline, preferably supporting federal government, law enforcement, or high-accountability reporting environments.
Demonstrated expertise in data pipeline design using ETL and ELT methodologies, managing end-to-end data flows across government systems of record.
Hands-on experience with batch and streaming data processing using Apache Kafka and Apache Spark.
Proficiency in data modeling using Star schema and Snowflake schema for data warehousing and statistical reporting workloads.
Experience with cloud data platforms on at least one major provider, including AWS Glue, Redshift, S3, Lambda; GCP BigQuery, Dataflow, Pub/Sub; or Azure Data Factory, Synapse Analytics, and Event Hubs.
Strong SQL skills; Python and/or R proficiency; experience with Databricks, Oracle OBIEE or OAS, VBA, and/or UiPath preferred.
Experience with ICE or DHS systems, including ENFORCE, IIDS, UIP, OBIEE or OAS, is a strong plus.
Familiarity with data quality frameworks, metadata management, data cataloging, and FedRAMP-authorized or classified cloud environments.
Ability to meet strict, high-accuracy delivery deadlines consistent with STU standard operating procedures and FOUO and LES data handling requirements.
Bachelor's Degree required.
Active ICE clearance required; preference for candidates currently cleared or cleared within the last two years.
Ability to obtain and maintain required clearance level is a condition of employment.

Nice To Haves

Master's Degree in a relevant technical discipline preferred.
Cloud data engineering certifications strongly preferred, including AWS Certified Data Engineer, Google Professional Data Engineer, or Microsoft Certified Azure Data Engineer Associate.
Apache Kafka, Spark, or Databricks certifications are a plus.
Excellent verbal and written communication skills; able to communicate data engineering findings and pipeline designs to both technical staff and non-technical federal stakeholders.
Ability to produce timely, accurate, and error-free deliverables consistent with FOUO and LES requirements and STU standard operating procedures.

Responsibilities

Design, build, and maintain robust data pipelines using ETL and ELT patterns to ingest, transform, and deliver data from ICE systems of record, including ENFORCE, IIDS, and related sources, to analytical and operational targets.
Develop and manage batch processing and real-time streaming data workflows using Apache Kafka and Apache Spark to support STU reporting cycles, including daily, weekly, and EOFY deliverables.
Implement and maintain dimensional data models using Star schema and Snowflake schema patterns to support STU statistical reporting, congressional deliverables, and machine learning workloads.
Build, configure, and manage cloud data platform infrastructure on AWS, GCP, and/or Azure, including data lakes, data warehouses, and serverless processing, consistent with FedRAMP and DHS and ICE data governance standards.
Create and maintain datasets, databases, automations, and reporting tools using SQL, Python, R, VBA, Databricks, Oracle OBIEE or OAS, and UiPath, as requested by federal stakeholders.
Facilitate the review, storage, and integration of data into ICE's various data analytics and engineering environments; perform ETL operations to transform raw data into formats suitable for STU analysts and data scientists.
Implement automated data quality reviews for data collected through ERO reporting and LESA reconciliation processes; ensure accuracy of data uploaded to UIP DQI Verify.
Design data pipelines with appropriate controls for fairness, transparency, and security while protecting sensitive law enforcement data in accordance with DHS privacy and data governance requirements.
Provide ad hoc after-hours support with data analytics and programming skills, including SQL, Python, R, VBA, Databricks, OAS, and UiPath, to support STU and DQI emergency taskings as requested.
Support EOFY Management data engineering activities, including ETL pauses, point-in-time reporting, database archival, population locking, and validation of new fiscal year reporting; coordinate with ITM OCIO on technical logistics.
Design and build data pipelines ensuring scalable, accurate data flow from multiple sources to data warehouses or lakes; design systems capable of handling large volumes of data as ICE reporting needs grow.
Complete documentation on data engineering practices, including standard operating procedures and continuity guides; provide training and support to STU users on data management tools and best practices.
Develop and execute User Acceptance Tests to validate enhancements to reporting databases and supporting tools; deliver UAT results at least monthly per release schedule.