Data Engineer

Jobtailor; Arlington (VA); On-site; USD 110,000 - 150,000; Full time

Job summary

Jobtailor in Arlington, VA seeks a seasoned Data Engineer to design, develop, test, deploy, and maintain enterprise ETL and data integration processes for analytical workloads. You will analyze workflows, optimize performance, and implement robust data models and validation routines to ensure data quality.

The role requires strong SQL, experience with enterprise ETL tools, and collaboration with BI and business teams to support dashboards and reports across complex data environments.

Qualifications

• Experience leading enterprise ETL development efforts in complex environments.
• Strong SQL and data-quality emphasis across large data warehouses.
• Ability to translate business requirements into robust data transformation logic.

Responsibilities

• Design, develop, test, deploy, and maintain enterprise ETL and data integration processes.
• Analyze existing ETL workflows and recommend redesign, simplification, consolidation, optimization, or replacement of legacy logic.
• Develop batch and incremental data loads from operational systems into analytical warehouse structures.
• Develop and maintain transformation logic using SQL, PL/SQL, ETL tools, scripting languages, or other data-engineering technologies.
• Design and support fact tables, dimension tables, star schemas, snowflake schemas, data marts, and other dimensional models.
• Implement slowly changing dimensions, surrogate keys, historical tracking, aggregation, lookup, and reference-data patterns.
• Develop source-to-target mappings, transformation specifications, load rules, dependencies, and technical documentation.
• Work with application and functional teams to understand source data, business rules, relationships, and analytical requirements.
• Build validation and reconciliation processes for data completeness, accuracy, consistency, and integrity.
• Troubleshoot failed ETL jobs, data-quality issues, transformation errors, duplicate or missing records, schema changes, and system discrepancies.
• Optimize ETL processing and database components for performance, scalability, reliability, and maintainability.
• Develop restart, recovery, exception-handling, logging, audit, and monitoring capabilities.
• Support scheduling and orchestration of ETL workflows, batch jobs, dependencies, and reporting processes.
• Assess impacts of source-system, application, database, and business-rule changes.
• Modernize legacy ETL technologies and data-processing patterns.
• Participate in testing, defect resolution, reconciliation, release, migration, and production-validation activities.
• Collaborate with BI developers to support 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

Skills

ETL Development

SQL Skills

Data Warehousing

Data Integration

Batch Processing

Incremental Loading

Performance Optimization

Root-Cause Analysis

Dimensional Data Modeling

Education

Bachelor's degree in Computer Science, Information Systems, Data Engineering, Engineering, or related field

Tools

Ab Initio

Informatica PowerCenter

Oracle Data Integrator

IBM DataStage

Talend

SSIS

Oracle Database

PL/SQL

Azure DevOps

BI Platforms

Job description

• Design, develop, test, deploy, and maintain enterprise ETL and data integration processes


• Analyze existing ETL workflows and recommend redesign, simplification, consolidation, optimization, or replacement of legacy logic


• Develop batch and incremental data loads from operational systems into analytical warehouse structures


• Develop and maintain transformation logic using SQL, PL/SQL, ETL tools, scripting languages, or other data-engineering technologies


• Design and support fact tables, dimension tables, star schemas, snowflake schemas, data marts, and other dimensional models


• Implement slowly changing dimensions, surrogate keys, historical tracking, aggregation, lookup, and reference-data patterns


• Develop source-to-target mappings, transformation specifications, load rules, dependencies, and technical documentation


• Work with application and functional teams to understand source data, business rules, relationships, and analytical requirements


• Build validation and reconciliation processes for data completeness, accuracy, consistency, and integrity


• Troubleshoot failed ETL jobs, data-quality issues, transformation errors, duplicate or missing records, schema changes, and system discrepancies


• Optimize ETL processing and database components for performance, scalability, reliability, and maintainability


• Develop restart, recovery, exception-handling, logging, audit, and monitoring capabilities


• Support scheduling and orchestration of ETL workflows, batch jobs, dependencies, and reporting processes


• Assess impacts of source-system, application, database, and business-rule changes


• Modernize legacy ETL technologies and data-processing patterns


• Participate in testing, defect resolution, reconciliation, release, migration, and production-validation activities


• Collaborate with BI developers to support 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

Requirements

• Must be a U.S. Citizen


• Must have 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 experience with Ab Initio, Informatica PowerCenter, Oracle Data Integrator, IBM DataStage, Talend, SSIS, or comparable tools


• Desired experience with Oracle Database and PL/SQL, dimensional data modeling, enterprise data warehouses, workload automation, data-quality frameworks, metadata management, BI platforms, Agile/SAFe, Azure DevOps, and secured Federal or DoD systems


• Related certifications are a plus

Core Competencies

Demonstrates expertise in ETL development, data integration, and data warehousing, with strong SQL skills and experience in designing complex data transformations and analytical data models. Proficient in troubleshooting ETL processes and ensuring data quality and integrity in enterprise environments.

Highest-signal resume keywords

• ETL Development


• SQL Skills


• Data Warehousing


• Data Integration


• Data Quality Assurance

Hard Skills

• ETL Processes


• Data Transformation


• Data Cleansing


• Data Validation


• Source-to-Target Mapping


• Dimensional Data Modeling


• Batch Processing


• Incremental Loading


• Performance Optimization


• Root-Cause Analysis

Soft Skills

• Collaboration


• Communication

Industry Keywords

• Data Engineering


• Enterprise Data


• Agile


• SAFe


• Federal Systems


• DoD Systems

Tools & Technologies

• Ab Initio


• Informatica PowerCenter


• Oracle Data Integrator


• IBM DataStage


• Talend


• SSIS


• Oracle Database


• PL/SQL


• Azure DevOps


• BI Platforms