{"id":3575218,"url":"https://alion.io/job/bridgestone-americas-data-engineer-nmfc","title":"Data Engineer - NMFC","company":{"id":1774680,"name":"Bridgestone Americas","domain":"bridgestoneamericas.com","url":"https://alion.io/company/bridgestoneamericas","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":95,"open_postings":9,"ghost_share":0,"stale_share":0.333,"repost_share":0.111,"time_to_fill_p50_days":21,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":45000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"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 S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Azure","optional":true},{"name":"Redis","optional":true}],"status":"live","first_seen_at":"2026-10-31T17:30:15Z","employer_posted_date":null,"last_verified_at":"2026-10-31T17:30:15Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Data Engineer\n\nOverview Of Role\n\n Design, develop, and maintain scalable, high-performance data engineering solutions using AWS,\n\nDatabricks, Spark, and PySpark, leveraging strong technical acumen to solve complex data and\n\nengineering challenges.\n\n Build robust data pipelines following Medallion Architecture (Raw, Silver, and Gold layers), covering data\n\ningestion, transformation, processing, data modeling, validation, quality checks, and reconciliation.\n\n Develop and optimize data solutions using AWS services including S3, Glue, Aurora/RDS, Lambda, and\n\nStep Functions, along with Databricks, Spark, and PySpark to improve performance, scalability, reliability,\n\nand cloud cost efficiency.\n\n Implement reliable orchestration and operational workflows covering scheduling, dependencies, retries,\n\nerror handling, monitoring, and failure recovery, while troubleshooting complex data and production\n\nissues and driving root-cause resolution.\n\n Develop reusable, maintainable, and production-ready code following engineering standards and best\n\npractices; contribute to code reviews, testing, CI/CD, deployment, automation, and continuous\n\nimprovement.\n\n Support data migration and modernization initiatives across AWS and Databricks, including legacy\n\nplatform migrations, source-to-target mapping, data validation, reconciliation, and production readiness.\n\n Collaborate with Product, Business, Architecture, QA, API, and Engineering teams in a cross-functional\n\nAgile environment, contributing to technical design discussions, estimation, sprint planning, backlog\n\nrefinement, and delivery.\n\n Provide technical guidance and mentorship to other engineers as applicable, promote reusable\n\nframeworks and engineering standards, and contribute to resolving complex technical challenges.\n\nRequired Qualifications\n\n 5+ years of experience in Data Engineering, ETL/ELT, and developing large-scale data pipelines, with\n\nexperience providing technical guidance or leadership as applicable.\n\n Strong hands-on experience with AWS services including S3, Glue, Aurora/RDS, Lambda, and Step\n\nFunctions, with a strong understanding of cloud-native data engineering practices.\n\n 2+ years of hands-on experience with Databricks, Spark, and PySpark, including Spark performance\n\noptimization, partitioning, joins, caching, file formats, data skew, and efficient job design.\n\n Strong SQL and Python/PySpark skills, with experience in data modeling, database design, schema\n\nmapping, ETL/ELT, and source-to-target transformations.\n\n Experience designing and optimizing data pipelines and orchestration workflows, including scheduling,\n\ndependencies, retries, error handling, monitoring, failure recovery, and performance optimization.\n\n Strong understanding of software engineering practices including coding standards, code reviews, testing,\n\nGit, CI/CD, Azure DevOps, reusable frameworks, and automation.\n\n Experience with data quality, validation, reconciliation, monitoring, troubleshooting, and root-cause\n\nanalysis.\n\n Understanding of REST APIs, API request/response flows, and integration with APIs and third-party source\n\nsystems.\n\n Experience creating, reviewing, and maintaining functional and technical documentation throughout the\n\ndelivery lifecycle.\n\n Strong communication and collaboration skills, with experience working across Product, Business,\n\nArchitecture, QA, API, and Engineering teams in Agile environments.\n\n Strong understanding of Agile practices, including sprint planning, backlog refinement, estimation,\n\niterative delivery, and production support.\n\n5\n\nPreferred Qualifications\n\n Experience with API development and integration, including hands-on experience working with API-driven\n\ndata solutions.\n\n Experience with Redis or other in-memory databases and caching technologies.\n Experience with Databricks and advanced Spark performance optimization techniques.\n Experience developing reusable frameworks, automation, and engineering standards.\n Relevant AWS certifications in Cloud, Data Engineering, or Solutions Architecture.\n Experience developing, debugging, and supporting data solutions within large, cross-functional\n\nengineering teams.\n\n Strong analytical and problem-solving skills, with the ability to manage multiple priorities in a deadlinedriven environment.\n Strong attention to detail and commitment to data quality, reliability, and engineering excellence","description_format":"text","description_chars":4390,"description_truncated":false,"requirements":{"experience_years_min":5,"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":["Plastics & Polymers","Automotive Components"],"lifecycle":[{"event":"open","at":"2026-10-31T20:09:45Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":1,"expected_fill_days":21,"reasons":["seen:1","velocity","win:early"],"computed_at":"2026-11-02T06:13:15Z"},"pay":null,"html_url":"https://alion.io/job/bridgestone-americas-data-engineer-nmfc","json_url":"https://alion.io/job/bridgestone-americas-data-engineer-nmfc.json","meta":{"generated_at":"2026-11-02T21:53:26Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":30641,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-03T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":1774680},"rest":"https://alion.io/mcp/rest/get_company?id=1774680"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fbridgestone-americas-data-engineer-nmfc"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fbridgestone-americas-data-engineer-nmfc"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fbridgestone-americas-data-engineer-nmfc"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/bridgestone-americas-data-engineer-nmfc\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fbridgestone-americas-data-engineer-nmfc"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3575218}},{"tool":"search_jobs","arguments":{"company":"bridgestoneamericas.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3575218},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. Docs: https://alion.io/developers"}}