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Data Engineer
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Data Engineer
- Richmond, Virginia, United States
- Richmond, Virginia, United States
Über
Design, build, and optimize scalable ETL/ELT pipelines that move data across on‑prem, cloud, and hybrid environments. Architect and manage enterprise data warehouses, data lakes, and Lakehouse solutions (Databricks, AWS/Azure). Write production‑quality SQL, Python, and Spark code for data transformation, enrichment, and validation. Implement and enforce data governance, lineage tracking, and cataloging standards across the organization. Ensure data quality through automated monitoring, testing frameworks, and SLA adherence. Partner with data analysts, data scientists, and business stakeholders to understand and fulfill data requirements. Support CI/CD practices and infrastructure‑as‑code for data platform deployments. Document data models, pipeline flows, and technical specifications to support knowledge transfer. Technical Skills
Languages & Querying: SQL (advanced), Python, PySpark, Bash/Shell, Scala. Cloud & Platforms: Microsoft Fabric, Azure Synapse, Azure Data Factory. Orchestration & Pipelines: Apache Airflow, dbt, Databricks, Kafka, Spark. Infrastructure & DevOps: Terraform, Docker, Kubernetes, GitHub Actions, CI/CD. Basic Qualifications
Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related quantitative field. 4+ years of experience in data engineering, data architecture, or a closely related role. 3+ years of demonstrated experience building and maintaining production data pipelines at scale. 3+ years of experience working in an enterprise IT environment. 3+ years of experience with advanced SQL and proficiency in at least one scripting language (Python strongly preferred). 3+ years of hands‑on experience with a major cloud data platform (AWS, Azure, or GCP). 3+ years of experience with workflow orchestration tools such as Apache Airflow or Azure Data Factory. Preferred Qualifications
Familiarity with streaming / real‑time data processing (Kafka, Fabric Event Streams, or Spark Streaming). Strong understanding of data modeling concepts and frameworks—star schema, OBT, Data Mesh. Familiarity with version control (Git) and software development best practices. Exposure to data governance frameworks and metadata management tools (Collibra, Alation). Cloud certifications (AWS Data Analytics, Azure Data Engineer Associate, or equivalent). Master’s degree in a relevant field. Strong analytical and problem‑solving skills with attention to data accuracy and quality. Effective communicator—able to translate complex technical concepts for non‑technical stakeholders. Collaborative team player comfortable working across cross‑functional teams. Self‑directed with ability to manage multiple priorities in a deadline‑driven environment. Pay Range
$98,614.00 - $167,644.00 (full‑time, Virginia Remote Office (VA99)). Equal‑Opportunity Employer
ICF is an equal‑opportunity employer. We consider qualified applicants with arrest and conviction records. Reasonable accommodations are available for disabled veterans, individuals with disabilities, and individuals with sincerely held religious beliefs for all phases of the application and employment process. For more information, please read our EEO policy.
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