{"id":3368856,"url":"https://alion.io/job/pcg-databricks-data-engineer-and-scientist","title":"Databricks Data Engineer and Scientist","company":{"id":4420385,"name":"PCG","domain":"parrainc.com","url":"https://alion.io/company/parrainc","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BambooHR","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gaithersburg, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":94000,"max_usd":203000,"period":"year","method":"role_country_seniority_unknown","sample_n":3718},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-27T00:00:00Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-30T08:36:12Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Parra Consulting Group (PCG) is seeking a Databricks Data Engineer and Scientist to support a federal client’s critical enterprise Lakehouse. This position designs, builds, and maintains robust data pipelines and applies data science, AI, and analytics skills to turn raw data into actionable insights across the business.\nThis successful candidate will be responsible for the following:\nDesign, build, and maintain robust, end-to-end data pipelines for an enterprise Lakehouse on Databricks and AWS.\nDevelop and manage ETL processes with comprehensive logging and error handling to troubleshoot and resolve issues.\nDesign data models within a Bronze, Silver, and Gold medallion architecture, selecting dimensional or relational approaches as appropriate.\nAnalyze and decompose complex legacy SQL, rebuild pipelines and models, and compare results to validate accuracy and performance.\nOptimize pipeline performance and scalability using techniques such as partitioning, bucketing, and caching.\nUse AI-assisted coding tools to accelerate pipeline analysis, data engineering, and data modeling tasks.\nHelp ensure data security and compliance, and collaborate with cross-functional teams to deliver analytics-ready data.\nRequired Qualifications\nBachelor’s degree in Computer Science, Computer Engineering, Engineering, Math, Physics, or Information Systems and Technology.\n8+ years of experience designing, developing, deploying, and managing ETL processes and data pipelines.\nAbility to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.\nS. citizenship required to support this federal contract.\nRequired Experience\nExperience designing, developing, deploying, and managing ETL processes and data pipelines with comprehensive logging and error handling.\n3+ years of experience building, debugging, and optimizing data pipelines using Databricks notebooks, clusters, and job orchestration tools, including Delta Lake and Unity Catalog.\n3+ years of experience writing Python and PySpark code for ETL scripts and custom transformations.\nExperience using AI-assisted coding tools, such as Claude Code or Cursor, to support data engineering and data modeling tasks.\nExperience with data modeling, including selecting dimensional or relational models, within a Bronze, Silver, and Gold medallion architecture.\nExperience using AWS services, including AWS Glue, Amazon S3, and Amazon RDS.\nKnowledge of ETL performance optimization techniques, such as partitioning, bucketing, and caching, and experience troubleshooting query performance.\nAbility to analyze and decompose complex legacy SQL, rebuild data pipelines or models, and compare results to validate accuracy and 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