{"id":3592359,"url":"https://alion.io/job/exavalu-data-engineering-lead","title":"Data Engineering Lead","company":{"id":3802017,"name":"Exavalu","domain":"exavalu.com","url":"https://alion.io/company/exavalu","size_band":"51-200","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","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":112000,"max_usd":220000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":450},"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":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Amazon Redshift","optional":true},{"name":"Apache Iceberg","optional":true},{"name":"DynamoDB","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-01T21:06:28Z","employer_posted_date":"2026-11-01","last_verified_at":"2026-11-05T15:07:12Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Job Title: Lead AWS Data Engineer\nNew Jersey - Newark area \n\nJob Description\nWe are seeking a Lead AWS Data Engineer to drive data engineering architecture, pipeline development, and technical delivery using AWS native services, Python, and PySpark. The role involves building scalable data products, modernizing enterprise data platforms, and providing technical leadership to data engineering teams.\nKey Responsibilities\nLead the design and development of scalable data pipelines using AWS Glue, EMR, S3, Python, and PySpark.\n\nDrive enterprise data integration, ETL/ELT workflows, and data product development.\n\nDefine engineering standards and conduct design and code reviews.\n\nOptimize pipeline performance, data quality, and processing scalability.\n\nGuide and mentor Data Engineers while collaborating with architecture, technology, and business teams.\n\nRequirements\nRequired Skills\nStrong experience in AWS Data Engineering, S3, Glue, and EMR.\n\nProficiency in Python, PySpark, SQL, and ETL/ELT.\n\nExpertise in data pipeline design, optimization, and enterprise data integration.\n\nExperience in technical leadership, code reviews, and team mentoring.\n\nPreferred Skills\nExperience with Amazon Redshift, Athena, and DynamoDB.\n\nKnowledge of Apache Iceberg and data lake/lakehouse architecture.\n\nExperience with domain-oriented data products and authoritative data sources.\n\nExposure to large-scale enterprise data modernization.\n\nBenefits\nExavalu also promotes flexibility, adapting to the needs of employees, customers, and the business. 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