Spatial Front, Inc
Data Engineer
Crystal City - Hybrid
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- Role family
- Data & ML
- Seniority
- Mid level
- Work mode
- On-site / unstated
- First seen by hirly
- 26 Sept 2026
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the posting
Description
Spatial Front, Inc. (SFI) is seeking a Data Engineer to support our growing modernization team. SFI was recently awarded the 2025 USA Today National Top Places to Work award and the 2025 Washington Post Top Workplaces. The ideal candidate will perform hands-on data engineering to design, modernize, optimize, and support enterprise Extract, Transform, and Load (ETL) processes and analytical data warehouse structures supporting PeopleSoft HCM and related enterprise systems.
This role is focused on the movement, transformation, quality, and organization of enterprise data for reporting and analytics. The candidate will analyze existing ETL processes, design improved data-loading approaches, develop and maintain transformation logic, and support dimensional data warehouse structures including star schemas, facts, dimensions, and data marts. The candidate will work closely with BI developers, DBAs, application teams, functional analysts, and infrastructure personnel to deliver reliable, scalable, and maintainable data pipelines for Federal Government customers.
Location
Crystal City, VA - On-Site/Hybrid
Responsibilities
- Design, develop, test, deploy, and maintain enterprise ETL and data integration processes supporting analytical data warehouses and reporting environments.
- Analyze existing ETL workflows and recommend opportunities to redesign, simplify, consolidate, optimize, or replace legacy data-processing logic.
- Develop batch and incremental data loads that extract data from operational systems, transform data according to business and technical rules, and load analytical warehouse structures.
- Develop and maintain transformation logic using SQL, PL/SQL, ETL development tools, scripting languages, or other appropriate data-engineering technologies.
- Design and support analytical data warehouse structures including fact tables, dimension tables, star schemas, snowflake schemas, data marts, and other dimensional models.
- Implement slowly changing dimensions, surrogate keys, historical tracking, aggregation, lookup, reference-data, and other common data warehouse patterns.
- Develop and maintain source-to-target mappings, transformation specifications, load rules, dependencies, and supporting technical documentation.
- Work with application and functional teams to understand source-system data structures, business rules, code values, relationships, and downstream analytical requirements.
- Build data-validation and reconciliation processes to confirm completeness, accuracy, consistency, and integrity between source systems, ETL processing, warehouse structures, and downstream reports.
- Troubleshoot failed ETL jobs, data-quality issues, transformation errors, duplicate or missing records, schema changes, and discrepancies between operational and analytical systems.
- Optimize ETL processing for performance, scalability, reliability, and maintainability, including SQL tuning, bulk-processing techniques, parallel execution, load sequencing, and efficient data movement.
- Work with DBAs to optimize database structures, indexes, partitions, statistics, materialized views, and other physical database components supporting warehouse performance.
- Develop restart, recovery, exception-handling, logging, audit, and monitoring capabilities for production ETL processes.
- Support scheduling and orchestration of ETL workflows, dependencies, batch jobs, and downstream reporting processes.
- Assess the impact of source-system changes, application upgrades, database changes, and business-rule changes on existing ETL and warehouse processes.
- Support modernization of legacy ETL technologies and data-processing patterns to more maintainable and supportable approaches.
- Participate in testing, defect resolution, data reconciliation, release, migration, and production-validation activities.
- Create and maintain technical documentation including ETL designs, source-to-target mappings, data models, job flows, transformation rules, deployment procedures, and operational support guidance.
- Collaborate with BI developers to ensure warehouse structures and data pipelines support required semantic models, reports, dashboards, and analytical use cases.
- Participate in Agile/SAFe activities including PI Planning, backlog refinement, iteration execution, demonstrations, testing, and release planning.
- Other duties as assigned.
Requirements
- Must be a U.S. Citizen with an active Secret security clearance or be able to obtain one.
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, Engineering, or a related field; equivalent relevant experience may be considered.
- 3+ years of hands-on data engineering, ETL development, data warehousing, database development, or related enterprise data experience.
- Strong hands-on experience designing, developing, troubleshooting, and supporting ETL processes in complex enterprise environments.
- Strong SQL skills and experience working with Oracle or comparable relational databases.
- Experience developing complex data transformations, joins, aggregations, lookups, data cleansing, validation, and reconciliation logic.
- Strong understanding of analytical data warehouse concepts including facts, dimensions, star schemas, snowflake schemas, data marts, surrogate keys, and slowly changing dimensions.
- Experience developing source-to-target mappings and translating business and technical requirements into data transformation and loading logic.
- Experience with batch processing, incremental loading, scheduling, dependencies, restart/recovery, error handling, and production support of ETL processes.
- Experience troubleshooting data-quality, ETL, SQL, performance, and data-integration issues through structured root-cause analysis.
- Understanding of database performance considerations including indexing, partitioning, query optimization, bulk processing, and large-volume data movement.
- Strong written and verbal communication skills and ability to collaborate effectively with BI, database, application, infrastructure, and business teams.
Desired Skills
- Hands-on experience with one or more enterprise ETL technologies such as Ab Initio, Informatica PowerCenter, Oracle Data Integrator (ODI), IBM DataStage, Talend, SSIS, or comparable data integration tools.
- Strong experience with Oracle Database and PL/SQL, including packages, procedures, functions, cursors, bulk processing, and performance tuning, is a plus.
- Experience developing ETL solutions implemented primarily through SQL and stored procedures as well as through commercial ETL platforms.
- Experience modernizing, replacing, or consolidating legacy ETL processes and data warehouse workloads.
- Strong experience with dimensional data modeling, including star schemas, conformed dimensions, fact-table design, slowly changing dimensions, and analytical data marts.
- Experience supporting large enterprise data warehouses with high-volume batch loads and complex source-system dependencies.
- Experience with Oracle database performance features such as partitioning, materialized views, parallel processing, bulk operations, and query optimization.
- Experience with job scheduling or workload automation technologies used to coordinate enterprise batch and ETL processing.
- Experience with data-quality frameworks, reconciliation processes, metadata management, lineage, or data-governance practices.
- Knowledge of PeopleSoft HCM data structures, Oracle-based enterprise applications, or HR/payroll data is a plus.
- Experience working with business intelligence and analytics teams using Oracle Analytics Server (OAS), Oracle Analytics Cloud (OAC), or comparable reporting platforms is a plus.
- Experience working in Agile or SAFe environments and using Azure DevOps (ADO) or a similar lifecycle-management tool.
- Experience supporting secured Federal or DoD enterprise systems is preferred.
- Oracle Database, data engineering, ETL, data wareho
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