{"id":3368857,"url":"https://alion.io/job/pcg-data-success-engineer","title":"Data Success Engineer","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":92000,"max_usd":201000,"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":"Agile","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"Databricks","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Confluence","optional":true},{"name":"Delta Lake","optional":true},{"name":"Jira","optional":true},{"name":"Scrum","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-27T00:00:00Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-30T17:28:02Z","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 Data Success Engineer to support a federal client’s enterprise data and analytics program. This position works at the intersection of business analysis and data engineering, partnering with stakeholders to turn mission needs into reliable, usable data products that help people make better decisions.\nThis successful candidate will be responsible for the following:\nPartner with business stakeholders, data owners, analysts, and technical teams to understand business processes and data needs.\nFacilitate information-gathering discussions, clarify requirements, and translate needs into user stories, acceptance criteria, source-to-target mappings, and technical specifications.\nBuild and improve the data pipelines that deliver data to business users, including solutions built with Databricks.\nUse SQL and Python to query, profile, transform, and validate data, and troubleshoot data quality issues across multiple tables and sources.\nEnsure data solutions meet business requirements and help clients understand how their data products support business outcomes.\nDocument data definitions and transformation logic, and explain technical findings in clear, non-technical language.\nContribute to Agile planning, sprint activities, and continuous improvement efforts.\nRequired Qualifications\nBachelor’s degree in Computer Science, Computer Engineering, Engineering, Math, Physics, or Information Systems and Technology.\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 gathering, analyzing, and documenting business or data requirements, including translating needs into user stories, acceptance criteria, source-to-target mappings, or technical specifications.\nExperience working directly with clients and stakeholders to facilitate information-gathering discussions, ask effective questions, clarify needs, and communicate findings.\nExperience with SQL, including writing complex queries and investigating data issues across multiple tables or sources.\nExperience using AWS services, including AWS Glue, Amazon S3, and Amazon RDS.\nExperience using Python for data processing, automation, or pipeline development.\nExperience working with relational databases and structured data.\nAbility to connect business objectives to data requirements and technical implementation.\nPreferred Qualifications\nExperience with Databricks, including notebooks, Spark, Delta Lake, or Databricks SQL.\nExperience with data warehousing, lakehouse architecture, or medallion data architecture.\nExperience with data quality frameworks, metadata management, or data governance.\nExperience with Agile delivery tools and practices, such as Jira, Confluence, and Scrum.\nExperience creating process flows, data models, or other artifacts that help teams understand how data moves and is used.\nStrong analytical, problem-solving, written, and verbal communication skills.\nDatabricks, AWS, or data engineering 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