{"id":4153482,"url":"https://alion.io/job/jpmorganchase-software-engineer-iii-python-databricks-and-aws-3","title":"Software Engineer III - Python, Databricks and AWS","company":{"id":257,"name":"JPMorganChase","domain":"jpmorganchase.com","url":"https://alion.io/company/jpmorganchase","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":88,"open_postings":1016,"ghost_share":0.009,"stale_share":0.628,"repost_share":0.048,"time_to_fill_p50_days":15,"computed_at":"2026-11-12T10:38:37Z"}},"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":["Plano, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"IAM","optional":false},{"name":"Least Privilege","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-11-10T18:33:49Z","employer_posted_date":"2026-11-10","last_verified_at":"2026-11-12T10:03:57Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.\nAs a Software Engineer at JPMorgan Chase within Corporate Technology - Global Finance Technology, you serve as a seasoned member of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.\nJob responsibilities\nDeliver ingestion at scale: implement resilient ingestion from AWS sources into Databricks (batch + streaming), including CDC where needed.\nBuild maintainable pipelines: use Delta Live Tables (DLT) and/or standard Jobs with clear modular structure, testing, and documentation.\nOperational excellence: productionize workloads via Databricks Workflows/Jobs, robust retries, checkpointing, idempotency, and safe re-runs.\nGovernance by design: enforce least privilege, data classification (PII), auditing, lineage/metadata, and controlled sharing/consumption.\nPerformance & cost management: tune Spark/Delta workloads, right-size clusters, optimize storage layout, and manage job/warehouse spend.\nCI/CD and IaC: Terraform (preferred) for Databricks + AWS resources; promotion across environments.Testing: unit/integration tests for transformations, data quality checks, contract testing, and replay/backfill procedures.\n\nVersion control & code review discipline; clear documentation and runbooks\nLeverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.\nApplies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.\nRequired qualifications, capabilities, and skills\nFormal training or certification on software engineering concepts and 5+ years hands on Software Development Life Cycle experience\nExperience in data engineering experience building and maintaining data pipelines.\nHands-on experience building and operating a Databricks Lakehouse Hosted in AWS\nExperience with Delta Lake (ACID tables, partitioning, schema evolution, \nProven experience with Spark on Databricks (performance tuning, cluster sizing, skew mitigation, joins, caching, file sizing).\nExperience with streaming and batch pipelines (Structured Streaming; incremental processing; backfills; late-arriving data).\nStrong AWS fundamentals for data platforms: S3, IAM, KMS, networking basics (VPC/security groups), logging/auditing.\nExperience implementing data governance/security controls in Databricks (e.g., Unity Catalog, table/column permissions, credential passthrough patterns as applicable)\nDemonstrate experience with reliability: monitoring/alerting, incident response, RCA, and SLO/SLA management\nUnderstanding of responsible AI use in 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