{"id":2068553,"url":"https://alion.io/job/jpmorganchase-data-engineer-iii-etl-2","title":"Data Engineer III - ETL","company":{"id":2649833,"name":"Campbell Global","domain":"campbellglobal.com","url":"https://alion.io/company/campbellglobal","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":91,"open_postings":212,"ghost_share":0.042,"stale_share":0.382,"repost_share":0.094,"time_to_fill_p50_days":13,"computed_at":"2026-11-05T05:54:30Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Jersey City, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":90000,"max_usd":173000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":352},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Bitbucket","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"SQL","optional":false},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-10-07T17:47:45Z","employer_posted_date":"2026-11-04","last_verified_at":"2026-11-05T07:52:36Z","board_verified":true,"closed_at":null,"days_open":28,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":28},"description":"Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.\nAs a Data Engineer III at JPMorganChase within the Corporate Technology , you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You are responsible for developing, testing, and maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.\nJob responsibilities\nSupports review of controls to ensure sufficient protection of enterprise data\nUses enterprise-authorized AI capabilities within the work environment to accelerate data pipeline/design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.\nResponsible for making configuration and customization changes to generate a product at business or customer requests and advising colleagues in requests\nUpdates logical or physical data models based on new use cases\nFrequently uses SQL and understands NoSQL databases and their niche in the marketplace\nApplies reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines (e.g., test generation and control validation), ensuring traceability/auditability and alignment to resiliency and security expectations.\nRequired qualifications, capabilities, and skills\nFormal training or certification on data engineering concepts and 3+ years applied experience in data engineering, with a track record of developing and deploying business critical pipelines in production.\nExperience across the data lifecycle with hands-on experience in building and optimizing ETL/ELT pipelines (performance tuning, partitioning, file sizing, and incremental loads)\nProficiency in SQL, including advanced techniques such as joins, analytics and window functions, and query optimization\nExperience working with Databricks Genie Spaces and ThoughtSpot integration to Databricks\nStrong Oracle experience, including DDL/DML and schema design best practices, and Oracle performance tuning (execution plans, indexes, partitioning, and statistics)\nExperience handling JSON and semi-structured data, including parsing, flattening, and schema 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permissions management, and lineage and metadata patterns\nUnderstanding of Datalake , Datamesh and Lakehouse architectures\nExposure to containerization and orchestration technologies such as Docker or Kubernetes\nFamiliarity with CI/CD tooling and DevOps practices\nKnowledge of financial services technology or regulated industry environments","description_format":"text","description_chars":3664,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Forest Resources","Asset Management & Funds","Land & Agriculture Property"],"lifecycle":[{"event":"open","at":"2026-10-08T05:07:17Z"},{"event":"close","at":"2026-10-10T16:12:59Z"},{"event":"reopen","at":"2026-11-04T04:12:39Z"}],"visa":[],"liveness":{"score":22,"band":"cold","label":"Long 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