{"id":4245773,"url":"https://alion.io/job/metlife-senior-big-data-engineer-i","title":"Senior Big Data Engineer - I","company":{"id":450553,"name":"MetLife","domain":"metlife.com","url":"https://alion.io/company/metlife-5","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Avature","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Cosmos DB","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Hadoop","optional":false},{"name":"HBase","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Apache NiFi","optional":true},{"name":"Azure DevOps","optional":true},{"name":"CI/CD","optional":true},{"name":"Git","optional":true},{"name":"Unix","optional":true}],"status":"live","first_seen_at":"2026-11-13T12:33:39Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T12:45:12Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Data Engineer\nThe Opportunity\nThe Data Engineer is responsible for designing, building, and delivering scalable data engineering solutions that enable advanced analytics, reporting, and business decision-making across the organization. This role plays a critical part in the data and analytics lifecycle by developing production-grade data platforms and pipelines leveraging Big Data technologies and cloud-based solutions.\nAs a senior individual contributor, this position is expected to independently solve complex business challenges, lead solution design and estimation activities, and drive engineering excellence across projects. The role provides an exciting opportunity to work with modern Azure data technologies, large-scale distributed systems, and real-time data processing frameworks while mentoring data engineers and collaborating with stakeholders across Business, Technology, Operations, and Data & Analytics functions.\nKey Responsibilities\nDesign, build, and maintain robust ETL/ELT pipelines across Azure cloud and on-premises environments for batch and real-time data processing.\nDevelop scalable solutions to collect, ingest, transform, and store large volumes of structured and unstructured data.\nIndependently lead solution architecture, technical design, effort estimation, and implementation planning for data engineering initiatives.\nMonitor, optimize, and troubleshoot data platforms and pipelines to ensure reliability, scalability, availability, and performance.\nImplement and enforce data quality, governance, security, compliance, and operational standards.\nBuild and support data lakes, data warehouses, data marts, and Medallion Architecture-based solutions.\nDevelop real-time and streaming data pipelines using Apache Spark and related technologies.\nCollaborate with cross-functional teams including Data Governance, Data Quality, Data Architecture, Data Modeling, Data Science, DevOps, Business Intelligence, Operations, and Technology groups.\nMentor and guide Data Engineers through technical leadership, knowledge sharing, and best practice adoption.\nDrive stakeholder engagement, provide technical recommendations, and effectively communicate complex technical solutions to business and technology audiences.\nRequired Qualifications\nBachelor's degree in Computer Science, Information Technology, Engineering, or an equivalent educational qualification.\n8-10+ years of experience in Data Engineering, Big Data, Cloud Data Platforms, or related domains.\nStrong expertise in SQL and Python and/or Scala for large-scale data processing and engineering solutions.\nExtensive experience in ETL/ELT pipeline design, development, solution architecture, and estimation.\nHands-on experience with Big Data technologies including Apache Spark, Hadoop, and Hive.\nStrong proficiency in Azure Data Engineering services including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Event Hub, and Azure Functions.\nExperience working with NoSQL and distributed databases such as Cosmos DB and HBase.\nDeep understanding of Data Lakes, Data Warehouses, Data Marts, and Medallion Architecture.\nStrong expertise in performance optimization, scalability improvements, and data quality validation.\nExperience designing and supporting both batch and real-time streaming data pipelines using Spark.\nExcellent communication, analytical thinking, structured problem-solving, storytelling, and stakeholder management skills.\nProven experience mentoring and developing junior and mid-level Data Engineers.\nAbility to work independently and drive end-to-end solution delivery in a senior individual contributor capacity.\nPreferred Qualifications\nExperience with DevOps practices including Git, Azure DevOps, and CI/CD pipeline implementation.\nKnowledge of Kafka, MongoDB, Apache NiFi, and Unix Shell Scripting.\nExposure to Generative AI technologies, AI-enabled data platforms, and emerging AI tools.\nExperience working within the Banking, Financial Services, and Insurance (BFSI) domain.\nAzure certifications in Data Engineering, Cloud Architecture, or related technologies.\nExperience leading cloud modernization, data transformation, and enterprise-scale analytics initiatives.\nStrong consulting mindset with the ability to influence technical and business stakeholders.\nExperience\n8-10+ Years of Relevant Experience\nEducation\nBachelor's Degree in Computer Science, Information Technology, Engineering, or Equivalent Educational 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