Data Engineer

Unissant•Washington, VA

119d•Onsite

About The Position

Unissant, Inc. is seeking a Data Engineer to support 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 and supports accurate, consistent reporting of ICE operations, including congressional and interagency data requests, FOIA responses, litigation needs, and reporting through the ICE Integrated Decision Support System (IIDS) and ENFORCE. The role provides data engineering infrastructure for STU analysts and data scientists. The Data Engineer designs, builds, and maintains data pipelines and processing workflows; develops dimensional data models; and configures cloud data platforms in accordance with applicable FedRAMP, DHS, and ICE requirements. The position also supports data quality reviews, reporting tools, EOFY activities, user acceptance testing, documentation, training, and occasional after-hours taskings. The role is on-site in the Washington, D.C. metropolitan area, with minimal travel expected. Work is primarily in a routine office environment. Candidates must have an active ICE clearance; the ability to obtain and maintain the required clearance is a condition of employment. Candidates will undergo pre-employment screening.

Requirements

3–10 years of experience in data engineering, data architecture, or a closely related discipline.
Bachelor’s degree required; preferred fields include Computer Science, Information Technology, Information Systems, Data Engineering, or a related discipline.
Demonstrated expertise in ETL and ELT data pipeline design and end-to-end data flows across government systems of record.
Hands-on experience with batch and streaming processing using Apache Kafka and Apache Spark.
Proficiency in Star schema and Snowflake schema data modeling for data warehousing and statistical reporting.
Experience with at least one major cloud data platform: AWS, GCP, or Azure.
Strong SQL skills and proficiency in Python and/or R.
Active ICE clearance required; ability to obtain and maintain the required clearance is a condition of employment.
Excellent verbal and written communication skills, including the ability to explain engineering findings and pipeline designs to technical staff and non-technical federal stakeholders.
Ability to produce timely, accurate, error-free deliverables consistent with FOUO and LES requirements and STU standard operating procedures.
Ability to work extended hours as needed.
Must undergo pre-employment screening.

Nice To Haves

Experience supporting federal government, law enforcement, or high-accountability reporting environments.
Experience with AWS Glue, Redshift, S3, or Lambda; GCP BigQuery, Dataflow, or Pub/Sub; or Azure Data Factory, Synapse Analytics, or Event Hubs.
Experience with Databricks, Oracle OBIEE or OAS, VBA, and/or UiPath.
Experience with ICE or DHS systems, including ENFORCE, IIDS, UIP, OBIEE, or OAS.
Familiarity with data quality frameworks, metadata management, data cataloging, and FedRAMP-authorized or classified cloud environments.
Master’s degree in a relevant technical discipline.
Cloud data engineering certification, such as AWS Certified Data Engineer, Google Professional Data Engineer, or Microsoft Certified Azure Data Engineer Associate.
Apache Kafka, Spark, or Databricks certification.
Active ICE clearance or clearance held within the last two years.

Responsibilities

Design, build, and maintain ETL and ELT pipelines that ingest, transform, and deliver data from ICE systems of record, including ENFORCE and IIDS, to analytical and operational targets.
Develop and manage batch-processing and real-time streaming workflows using Apache Kafka and Apache Spark for STU reporting cycles, including daily, weekly, and EOFY deliverables.
Implement and maintain Star schema and Snowflake schema dimensional data models for statistical reporting, congressional deliverables, and machine learning workloads.
Build, configure, and manage cloud data platform infrastructure, 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 review, storage, and integration of data into ICE analytics and engineering environments, and transform raw data into formats suitable for STU analysts and data scientists.
Implement automated data quality reviews for ERO reporting and LESA reconciliation processes, and ensure accuracy of data uploaded to UIP DQI Verify.
Design pipelines with controls for fairness, transparency, and security, protecting sensitive law enforcement data in accordance with DHS privacy and data governance requirements.
Provide ad hoc after-hours analytics and programming support for STU and DQI emergency taskings, using relevant tools and programming skills as requested.
Support EOFY Management data engineering, including ETL pauses, point-in-time reporting, database archival, population locking, and validation of new fiscal-year reporting; coordinate technical logistics with ITM OCIO.
Design scalable pipelines to move accurate data from multiple sources to data warehouses or lakes and handle growing ICE reporting volumes.
Document data engineering practices, including standard operating procedures and continuity guides, and train and support STU users on data management tools and best practices.
Develop and execute User Acceptance Tests for reporting database and tool enhancements, and deliver UAT results at least monthly according to the release schedule.
Meet strict delivery deadlines and produce accurate deliverables consistent with STU procedures and FOUO and LES data-handling requirements.