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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** ICF Consulting Group, Inc. - **Location:** Atlanta, GA, United States - **Experience:** Experienced - **Salary:** $98,614.0 - $167,644.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Bioinformatics, Cloud Database, Cloud Engineering, Cloud Storage, Databases, Information Engineering, Data Integration, Data Systems, Apache Hive, Python (Programming Language), NumPy, SAS (Software), SQL Databases, Subversion, XPath, Extensible Stylesheet Language Transformations (XSLT), Data Processing, Google Cloud, Cloud Platform System, Git, Pandas, Matplotlib, Data Lakes, Pyspark, Information Technology, Plotly, Tools for Reporting, Software Version Control, Data Pipelines, Serverless Computing - **Published:** June 25, 2026 - **Apply:** https://www.dice.com/job-detail/bc685b60-36e5-423f-99b5-865a6421ca14 ## About the Role * Position requires a minimum of 2 years of experience in data engineering or working with healthcare data environments * BA/BS in computer science, Data Science, Statistics, Public Health Informatics, Bioinformatics, or related field * The position requires strong expertise in data integration, transformation, quality control, and the delivery of production-ready data for analytics and reporting platforms. * Demonstrated hands-on experience with Python, PySpark, Spark SQL, and commonly used Python libraries for data processing and analysis * Experience with Python libraries such as pandas, NumPy, PyArrow, matplotlib, Plotly, or similar tools * Position requires experience with cloud platforms such as AWS, Azure, Google Cloud, or similar cloud environments * Experience handling large databases and high-volume datasets (millions+ records) * Must have experience with SAS and/or R * Experience implementing data quality validation and QC frameworks * Strong analytical, troubleshooting, and problem-solving skills * Must have the ability to obtain and maintain a Public Trust Preferred Skills/Experience: * Experience with XML/XSLT/XML path * Proven experience migrating SAS-based pipelines to Python/PySpark or cloud-native architectures * Experience with cloud-based data platforms, data lakes, cloud storage, serverless functions, and containerized applications. * Experience developing and optimizing PySpark pipelines for large-scale data processing * Version control with (Example: Git, SVN) Professional Experience: * Works well in a team environment and values the expertise and of others * Understands the value of processes and protocol, and is willing to follow them * Excellent written and verbal communication skills * Strong analytical and problem-solving skills ## Description ICF is seeking a detail-oriented Data Engineer to support the development, optimization, and deployment of large-scale healthcare data pipelines and analytical datasets. This role will focus on cancer registry and population-based data systems. As part of the team contributing to the fight against cancer, you will work with high-volume, complex structured datasets using NAACCR registry-standard formats. ICF partners with the Centers for Disease Control and Prevention (CDC) to monitor cancer diagnoses, incidence rates, geographic distribution, and treatment patterns. These efforts enable researchers, clinicians, and policymakers to better understand and combat cancer. In this role, you may also have the opportunity to support a diverse range of projects across multiple clients and subject areas, allowing you to expand your technical expertise and gain new skills. Historically, most of our projects are small to medium in size, providing team members with the opportunity to play an active role throughout the full project lifecycle-from requirements gathering and design to implementation, validation, and maintenance. This position can be based in Rockville, MD or Atlanta, GA and offers a hybrid work arrangement, with 2-3 days per week onsite at the ICF office., * Design, develop, and maintain scalable, cloud-based data pipelines using Python, PySpark, and SQL in cloud environments * Process and standardize large-scale healthcare datasets, including cancer registry, mortality, and population data * Develop and maintain production databases, analytic datasets, and reporting tables for statistical analysis and surveillance * Perform rigorous data quality validation, reconciliation, and consistency checks across large datasets * Collaborate with epidemiologists, statisticians, and analysts to design and implement data solutions for analytics needs * Troubleshoot data pipeline failures and large-scale data processing issues ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Scrape, Train, Predict: The Lifecycle of Data for AI Applications](https://www.wearedevelopers.com/videos/1652-scrape-train-predict-the-lifecycle-of-data-for-ai-applications) - [Vectorize all the things! 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