{"schemaVersion":"jobsearcher.job.v1","id":"459ec8ef2801bcd30c5dab9c","url":"https://jobsearcher.com/jobs/459ec8ef2801bcd30c5dab9c","canonicalUrl":"https://jobsearcher.com/jobs/459ec8ef2801bcd30c5dab9c","title":"Data Engineer, Analytics","description":"Permanent W-2 Employee / Corp2Corp Contractor | Omm IT Solutions | United States\r\nPosted On 07/13/2026\r\nJob Information\r\nStart Date 07/15/2026 12:00 AM\r\nCompensation Negotiable\r\nIT Services\r\nWork Authorization USC/GC/H1B/H4-EAD\r\nJob Opening ID Omm2971J\r\nState/Province Virginia\r\nCity Mc Lean\r\n22101\r\nJob Description\r\nPLEASE NOTE: IT IS 100% ON SITE POSITION IN Mc Lean VA\r\nKEY REQUIRED SKILLS\r\nPySpark & Python for data pipeline development, Snowflake & AWS\r\nWe are seeking a hands-on, delivery-focused Senior Data Engineer to help build and scale our cloud data platform. In this role, you will design and develop modern data pipelines using PySpark, Snowflake, and AWS to optimize cloud data workloads. The ideal candidate combines strong engineering fundamentals with cloud-native data expertise and is capable of translating complex business needs into robust, performant, and well-documented data solutions. Experience within Fannie Mae, Freddie Mac, or equivalent GSE/mortgage enterprise environments is highly valued.\r\nRESPONSIBILITIES\r\nScalable Architecture: Design and build scalable batch and streaming data pipelines using PySpark for large-scale data processing.\r\nModernization: Migrate legacy, on-premises ETL workloads (e.g., IBM DataStage, Informatica) to high-performing PySpark and Snowflake cloud pipelines.\r\nData Transformation: Write production-grade PySpark code to read from Amazon S3 (Parquet/Delta files), execute complex transformations, and process massive datasets efficiently.\r\nDeduplication: Design and implement robust deduplication strategies for high-volume datasets using PySpark.\r\nPlatform Engineering: Build and manage Snowflake warehouses, schemas, and data models optimized for enterprise analytics and business intelligence reporting.\r\nIceberg Tables: Design and implement Apache Iceberg tables in Snowflake to support open lakehouse architectures and data interoperability.\r\nIncremental Processing: Build and maintain Snowflake Dynamic Tables and Materialized Views to enable near real-time analytics and query acceleration.\r\nPySpark Tuning: Optimize distributed Spark jobs by leveraging partitioning, caching, broadcast joins, and shuffle optimization.\r\nSnowflake Optimization: Tune Snowflake workloads using clustering keys, micro-partition pruning, query profiling, precise warehouse sizing, and strategic result caching.\r\nCost Management: Continuously monitor and optimize Spark jobs, Snowflake queries, and AWS infrastructure to balance speed and cloud expenditure.\r\nData Quality: Implement data validation, lineage tracking, and monitoring solutions across all pipeline stages to ensure high data integrity.\r\nCross-Functional Collaboration: Partner closely with data architects, business analysts, Technical Program Managers (TPMs), and corporate stakeholders to deliver dependable data products.\r\nTechnical Documentation: Author comprehensive technical designs, data schemas, and operational runbooks to ensure every pipeline is maintainable and audit-ready.\r\nRequirements\r\nREQUIRED QUALIFICATION\r\nExperience: 6+ years of hands-on data engineering experience in large-scale enterprise environments.\r\nPySpark Expertise: Deep proficiency in building distributed data processing pipelines, handling S3 Parquet/Delta files, and implementing complex transformations and deduplication logic.\r\nSnowflake Proficiency: Strong hands-on experience with SnowSQL, Snowpipe, Streams, Tasks, and Role-Based Access Control (RBAC). Proven track record establishing Iceberg tables, Dynamic Tables, and Materialized Views.\r\nAWS Cloud Ecosystem: Robust working knowledge of AWS services, including S3, Glue, EMR, Lambda, IAM, Step Functions, CloudWatch, and Redshift.\r\nAdvanced SQL & Python: Mastery of advanced SQL techniques (window functions, CTEs, complex joins) alongside strong Python programming skills for automation, scripting, and orchestration utilities.\r\nOrchestration & Architecture: Solid understanding of data warehousing, ELT/ETL patterns, data lakes, and lakehouse architectures using tools like Airflow or AWS Step Functions.\r\nCommunication: Strong verbal and written communication skills with the ability to articulate technical decisions clearly to both technical peers and business leaders.\r\nPREFERRED QUALIFICATION\r\nIndustry Experience: Prior experience working within heavily regulated environments such as financial services, mortgage banking, or GSE programs (Fannie Mae / Freddie Mac).\r\nETL Migration: Hands-on experience with legacy ETL frameworks (e.g., IBM DataStage) to support modernization initiatives.\r\nDevOps & CI/CD: Familiarity with continuous integration and continuous deployment pipelines for data infrastructure (Git, Jenkins, GitHub Actions, Terraform).\r\nData Quality Frameworks: Exposure to automated data quality and validation frameworks (e.g., Great Expectations, dbt testing suites).\r\nStreaming Analytics: Knowledge of real-time streaming platforms like Apache Kafka or AWS Kinesis.\r\nProfessional Certifications: AWS Certified Data Analytics, AWS Certified Solutions Architect, or SnowPro Core/Advanced certifications.\r\nEducation/Work Experience\r\nExperience: 6+ years of hands-on data engineering experience in large-scale enterprise environments.\r\nJ-18808-Ljbffr","company":"Omm It Solutions","rawCompany":"omm it solutions","city":"Bismarck","state":"ND","isRemote":false,"isActive":false,"createdAt":"2026-08-08T01:30:09.277Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer, Analytics","description":"Permanent W-2 Employee / Corp2Corp Contractor | Omm IT Solutions | United States\r\nPosted On 07/13/2026\r\nJob Information\r\nStart Date 07/15/2026 12:00 AM\r\nCompensation Negotiable\r\nIT Services\r\nWork Authorization USC/GC/H1B/H4-EAD\r\nJob Opening ID Omm2971J\r\nState/Province Virginia\r\nCity Mc Lean\r\n22101\r\nJob Description\r\nPLEASE NOTE: IT IS 100% ON SITE POSITION IN Mc Lean VA\r\nKEY REQUIRED SKILLS\r\nPySpark & Python for data pipeline development, Snowflake & AWS\r\nWe are seeking a hands-on, delivery-focused Senior Data Engineer to help build and scale our cloud data platform. In this role, you will design and develop modern data pipelines using PySpark, Snowflake, and AWS to optimize cloud data workloads. The ideal candidate combines strong engineering fundamentals with cloud-native data expertise and is capable of translating complex business needs into robust, performant, and well-documented data solutions. Experience within Fannie Mae, Freddie Mac, or equivalent GSE/mortgage enterprise environments is highly valued.\r\nRESPONSIBILITIES\r\nScalable Architecture: Design and build scalable batch and streaming data pipelines using PySpark for large-scale data processing.\r\nModernization: Migrate legacy, on-premises ETL workloads (e.g., IBM DataStage, Informatica) to high-performing PySpark and Snowflake cloud pipelines.\r\nData Transformation: Write production-grade PySpark code to read from Amazon S3 (Parquet/Delta files), execute complex transformations, and process massive datasets efficiently.\r\nDeduplication: Design and implement robust deduplication strategies for high-volume datasets using PySpark.\r\nPlatform Engineering: Build and manage Snowflake warehouses, schemas, and data models optimized for enterprise analytics and business intelligence reporting.\r\nIceberg Tables: Design and implement Apache Iceberg tables in Snowflake to support open lakehouse architectures and data interoperability.\r\nIncremental Processing: Build and maintain Snowflake Dynamic Tables and Materialized Views to enable near real-time analytics and query acceleration.\r\nPySpark Tuning: Optimize distributed Spark jobs by leveraging partitioning, caching, broadcast joins, and shuffle optimization.\r\nSnowflake Optimization: Tune Snowflake workloads using clustering keys, micro-partition pruning, query profiling, precise warehouse sizing, and strategic result caching.\r\nCost Management: Continuously monitor and optimize Spark jobs, Snowflake queries, and AWS infrastructure to balance speed and cloud expenditure.\r\nData Quality: Implement data validation, lineage tracking, and monitoring solutions across all pipeline stages to ensure high data integrity.\r\nCross-Functional Collaboration: Partner closely with data architects, business analysts, Technical Program Managers (TPMs), and corporate stakeholders to deliver dependable data products.\r\nTechnical Documentation: Author comprehensive technical designs, data schemas, and operational runbooks to ensure every pipeline is maintainable and audit-ready.\r\nRequirements\r\nREQUIRED QUALIFICATION\r\nExperience: 6+ years of hands-on data engineering experience in large-scale enterprise environments.\r\nPySpark Expertise: Deep proficiency in building distributed data processing pipelines, handling S3 Parquet/Delta files, and implementing complex transformations and deduplication logic.\r\nSnowflake Proficiency: Strong hands-on experience with SnowSQL, Snowpipe, Streams, Tasks, and Role-Based Access Control (RBAC). Proven track record establishing Iceberg tables, Dynamic Tables, and Materialized Views.\r\nAWS Cloud Ecosystem: Robust working knowledge of AWS services, including S3, Glue, EMR, Lambda, IAM, Step Functions, CloudWatch, and Redshift.\r\nAdvanced SQL & Python: Mastery of advanced SQL techniques (window functions, CTEs, complex joins) alongside strong Python programming skills for automation, scripting, and orchestration utilities.\r\nOrchestration & Architecture: Solid understanding of data warehousing, ELT/ETL patterns, data lakes, and lakehouse architectures using tools like Airflow or AWS Step Functions.\r\nCommunication: Strong verbal and written communication skills with the ability to articulate technical decisions clearly to both technical peers and business leaders.\r\nPREFERRED QUALIFICATION\r\nIndustry Experience: Prior experience working within heavily regulated environments such as financial services, mortgage banking, or GSE programs (Fannie Mae / Freddie Mac).\r\nETL Migration: Hands-on experience with legacy ETL frameworks (e.g., IBM DataStage) to support modernization initiatives.\r\nDevOps & CI/CD: Familiarity with continuous integration and continuous deployment pipelines for data infrastructure (Git, Jenkins, GitHub Actions, Terraform).\r\nData Quality Frameworks: Exposure to automated data quality and validation frameworks (e.g., Great Expectations, dbt testing suites).\r\nStreaming Analytics: Knowledge of real-time streaming platforms like Apache Kafka or AWS Kinesis.\r\nProfessional Certifications: AWS Certified Data Analytics, AWS Certified Solutions Architect, or SnowPro Core/Advanced certifications.\r\nEducation/Work Experience\r\nExperience: 6+ years of hands-on data engineering experience in large-scale enterprise environments.\r\nJ-18808-Ljbffr","datePosted":"2026-08-08T01:30:09.277Z","dateModified":"2026-08-08T01:30:09.277Z","hiringOrganization":{"@type":"Organization","name":"Omm It Solutions","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bismarck","addressRegion":"ND","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"459ec8ef2801bcd30c5dab9c"},"url":"https://jobsearcher.com/jobs/459ec8ef2801bcd30c5dab9c"}}