Data Engineer Security Clearance

Position: Data Engineer with Security Clearance
Unissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results for our clients. Working collaboratively, we advance missions and careers through a focus on honesty, integrity, and dependability. We continuously look for talent, excited to join that effort. To learn more about our exciting organization, please visit us at  We are seeking a Data Engineer to join our 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 serves as ICE's official statistical reporting unit, ensuring accountability, consistency, and accuracy in the reporting of ICE operations.

STU maintains critical reports and queries, supports congressional and interagency data requests, FOIA responses, litigation needs, and continuous reporting improvements through the ICE Integrated Decision Support System (IIDS) and ENFORCE. The ideal candidate will bring strong technical expertise in data pipeline development, batch and streaming architecture, data modeling, and cloud data platforms to provide the infrastructure foundation that enables STU analysts and data scientists to deliver accurate and timely statistical reporting.

Essential Duties and 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.
Work Experience and Job

Skills:

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 Big Query, 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…