{"id":3517610,"url":"https://alion.io/job/campbell-global-lead-software-engineer-pythondatapysparkaws","title":"Lead Software Engineer - Python/Data/PySpark/AWS","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":95,"open_postings":150,"ghost_share":0.067,"stale_share":0.187,"repost_share":0.12,"time_to_fill_p50_days":13,"computed_at":"2026-11-01T06:10:25Z"}},"role":"Backend","role_family":"Backend","seniority":"lead","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":{"min_usd":115000,"max_usd":231000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1231},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon Aurora","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Bitbucket","optional":false},{"name":"CI/CD","optional":false},{"name":"Datadog","optional":false},{"name":"Db2","optional":false},{"name":"Dynatrace","optional":false},{"name":"Java","optional":false},{"name":"Jenkins","optional":false},{"name":"Machine Learning","optional":false},{"name":"Oracle","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spinnaker","optional":false},{"name":"Splunk","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"AWS Glue","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-26T18:58:52Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-11-01T15:50:03Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.\nAs a Lead Software Engineer at JPMorganChase within the Consumer & Community Banking, JPMWM Tech, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.\nJob responsibilities:\nExecutes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems\nCreates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems\nProduces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development\nGathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems\nProactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture\nContributes to software engineering communities of practice and events that explore new and emerging technologies\nDrives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.\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.\nAdds to team culture of diversity, equity, inclusion, and respect\nDetects, troubleshoots and Resolves Production issues in an Enterprise multi-environment settings using advanced observability tools\nRequired qualifications, capabilities, and skills:\nFormal training or certification on software engineering concepts and 5+ years applied experience \nHands-on practical experience in system design, application development, testing, and operational stability\nProficient in coding in one or more languages - Java, Python\nProficient in private and public Cloud hosted Platform - Pivotal Cloud, AWS. In-depth knowledge is a must for AWS ECS, S3, SQS, SNS, Lambda, Glue, pySpark, cloudwatch\nExperienced in SRE and Observability tools - Splunk, Dynatrace and Datadog\nProficient in Oracle, DB2 and AW Aurora Postgress Database. 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