{"id":3094948,"url":"https://alion.io/job/exl-lead-data-engineer-3","title":"Lead Data Engineer","company":{"id":38016,"name":"EXL","domain":"exlservice.com","url":"https://alion.io/company/exl","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":75,"open_postings":233,"ghost_share":0,"stale_share":0.996,"repost_share":0,"time_to_fill_p50_days":27,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Data Science","role_family":"Data Science","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":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":112000,"max_usd":221000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":450},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Apache Kafka","optional":true},{"name":"CI/CD","optional":true},{"name":"Hadoop","optional":true},{"name":"HBase","optional":true},{"name":"Looker","optional":true},{"name":"Power BI","optional":true},{"name":"Spark","optional":true},{"name":"Tableau","optional":true}],"status":"live","first_seen_at":"2026-08-05T19:24:38Z","employer_posted_date":"2026-08-05","last_verified_at":"2026-11-02T07:33:43Z","board_verified":true,"closed_at":null,"days_open":88,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":88},"description":"EXL is seeking a Senior Data Engineer to join our Data & Analytics practice and support strategic client engagements. This role will be responsible for designing, building, and managing scalable cloud-based data platforms, driving modern data engineering practices, and leading teams delivering high-impact data solutions. The ideal candidate will combine strong technical expertise with consulting and leadership capabilities, partnering closely with client stakeholders to translate business requirements into scalable data architectures and engineering solutions.\nData Engineering & Platform Development\nDesign, develop, and maintain scalable data pipelines and data products supporting analytics, reporting, AI, and operational use cases.\nBuild and optimize ETL/ELT frameworks for large-scale data ingestion, transformation, validation, and consumption.\nDevelop and manage cloud-native data platforms leveraging Snowflake, AWS, Apache Airflow and modern data architectures.\nCreate scalable data models, data marts, semantic layers, and curated datasets that support enterprise analytics initiatives.\nOptimize SQL workloads, transformation logic, and query performance to improve scalability and cost efficiency.\nEstablish reusable engineering frameworks, accelerators, and best practices to improve delivery consistency across projects.\nEnsure high standards of data quality, reliability, governance, and observability throughout the data lifecycle.\nDevelop and maintain Snowflake-based data ecosystems, leveraging advanced features for performance optimization and data sharing.\nBuild and orchestrate data workflows using Airflow and other workflow scheduling platforms.\nCollaborate directly with client stakeholders to gather requirements, define roadmaps, and develop scalable technical solutions.\nPresent solution designs, technical recommendations, and project updates to both technical and business audiences.\nPrepare and maintain comprehensive project documentation, technical specifications, architecture diagrams, and operational runbooks.\n Required Qualifications\n4+ years of experience in Data Engineering, Big Data Engineering, or Cloud Data Platform development.\nBachelor's or Master's degree in Computer Science, Engineering, Analytics, Mathematics, Information Systems, or related disciplines.\nStrong hands-on expertise in SQL, Python, and PySpark.\nExtensive experience working with Snowflake, Databricks, or similar cloud-native data platforms.\nProven experience building and supporting large-scale ETL/ELT data pipelines.\nStrong understanding of data warehousing concepts, dimensional modeling, and modern Lakehouse architectures.\nExperience implementing Medallion Architecture and enterprise-grade data modeling practices.\nHands-on experience with workflow orchestration tools such as Apache Airflow or equivalent scheduling frameworks.\nExperience working with cloud ecosystems including AWS, Azure, or GCP.\nStrong knowledge of performance tuning, optimization, monitoring, and operational support for data platforms.\nDemonstrated experience leading engineering teams and coordinating with client and internal stakeholders.\nExcellent analytical, problem-solving, communication, and stakeholder management skills.\nAbility to work independently and lead complex initiatives in fast-paced consulting environments.\nPreferred Qualifications\n\nExperience with streaming and real-time data processing frameworks.\nFamiliarity with DataOps, CI/CD, Infrastructure as Code, and DevOps practices.\nExperience with data governance, data quality frameworks, and metadata management.\nExposure to AI/ML data pipelines and feature engineering workflows.\nExperience with visualization tools such as Tableau, Power BI, or Looker.\nHands-on experience with Big Data technologies including Spark, Hadoop, Hive, HBase, Kafka, or related platforms.\nConsulting or client-facing delivery experience in enterprise-scale 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