{"id":3039388,"url":"https://alion.io/job/exl-lead-data-engineer-data-modeler","title":"Lead Data Engineer - Data Modeler","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":80,"open_postings":252,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":15,"computed_at":"2026-10-24T06:02:35Z"}},"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":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":28000,"max_usd":61000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":20},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EC2","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Git","optional":false},{"name":"Java","optional":false},{"name":"Jenkins","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false}],"status":"live","first_seen_at":"2026-05-21T09:12:29Z","employer_posted_date":"2026-05-21","last_verified_at":"2026-10-24T11:27:04Z","board_verified":true,"closed_at":null,"days_open":156,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":155},"description":"Our mission at LendingClub is to empower those who strive to achieve better\nfinancial health. Data intelligence team plays a crucial role in achieving our\nmission.\nWe are seeking a Lear Data Modeling Engineer for our Data team to provide data\nmodeling, data processing, and pipeline orchestration capabilities. You’ll be part of\nthe Data Intelligence organization that helps drive business decisions using data.\nYou will have the opportunity to use your expertise in data modeling, software\ndevelopment, design thinking, and analytical skills to build scalable data pipelines,\nrobust data models, and high-quality data products leveraging our PB-scale data.\nThis role is primarily focused on data modeling, with strong ownership of building\nand supporting the data pipelines and systems that operationalize those models.\nYou will be responsible for designing and evolving data models in a centralized\ndata warehouse, ensuring they are scalable, performant, and aligned with business\nneeds. In parallel, you will contribute to engineering development to ensure\nreliable data ingestion, transformation, and delivery.\nYou will also play a key role in driving data standardization efforts, establishing\nconsistent definitions, modeling patterns, and data quality practices across the\norganization.\nWhat you’ll do:\nDesign, develop, and maintain scalable, high-quality data models in a\ncentralized data warehouse (primary focus)\nTranslate business requirements into well-structured, reusable data models\nthat support analytics and downstream applications\nDefine and enforce data modeling standards, naming conventions, and best\npractices across domains\nLead and contribute to data standardization initiatives to ensure\nconsistency and interoperability of data assets\nBuild and maintain data pipelines that support and operationalize data\nmodels (ingestion, transformation, and delivery)\nDevelop pipelines that transform raw data into clean, well-modeled,\nanalytics-ready datasets\nCollaborate with Product, Engineering, and Program teams to deliver endto-end data solutions (models + pipelines)\nOptimize data models and pipelines for performance, scalability, and cost\nefficiency\nImplement processes for data validation, quality monitoring, and reliability\nWrite high-quality, testable code; adopt TDD and contribute to engineering\ndocumentation and best practices\nPerform root cause analysis on data and pipeline issues to improve system\nrobustness\nAbout you:\n10+ years of experience and a bachelor’s degree in Computer Science,\nInformation Systems, or related field; or equivalent experience\nStrong expertise in data modeling (dimensional modeling, warehouse\ndesign, normalization techniques)\nProven experience designing and implementing data models in\ncentralized/cloud data warehouses (Databricks, Snowflake, Redshift, etc.)\nSolid experience in data engineering and pipeline development to support\nmodeled data layers\n5+ years of experience with Databricks and DBT\nExperience with orchestration tools such as Airflow or Dagster\nIn-depth experience with distributed systems such as Spark\nStrong programming skills (Java, Scala, Python) with experience building\nproduction-grade data pipelines\nExperience with AWS cloud services (EC2, EMR, RDS)\nStrong understanding of data standardization, data governance, and data\nquality best practices\nExperience with Git, JIRA, Jenkins, and CI/CD pipelines\nExperience working with cross-functional teams in a dynamic environment\nYou are passionate about data modeling and designing scalable, wellstructured datasets\nYou are equally comfortable implementing pipelines that bring those\nmodels to life\nYou think in terms of data consistency, reusability, and long-term\nmaintainability\nYou value clean design, simplicity, and high-quality engineering practices\nYou have a track record of delivering reliable, well-modeled, production - ready data solutions\nDesign, develop, and maintain scalable, high-quality data models in a\ncentralized data warehouse (primary focus)\nTranslate business requirements into well-structured, reusable data models\nthat support analytics and downstream applications\nDefine and enforce data modeling standards, naming conventions, and best\npractices across domains\nLead and contribute to data standardization initiatives to ensure\nconsistency and interoperability of data assets\nBuild and maintain data pipelines that support and operationalize data\nmodels (ingestion, transformation, and delivery)\nDevelop pipelines that transform raw data into clean, well-modeled,\nanalytics-ready datasets\nCollaborate with Product, Engineering, and Program teams to deliver endto-end data solutions (models + pipelines)\nOptimize data models and pipelines for performance, scalability, and cost\nefficiency\nImplement processes for data validation, quality monitoring, and reliability\nWrite high-quality, testable code; adopt TDD and contribute to engineering\ndocumentation and best practices\nPerform root cause analysis on data and pipeline issues to improve system\nrobustness\nAbout you:\n10+ years of experience and a bachelor’s degree in Computer Science,\nInformation Systems, or related field; or equivalent experience\nStrong expertise in data modeling (dimensional modeling, warehouse\ndesign, normalization techniques)\nProven experience designing and implementing data models in\ncentralized/cloud data warehouses (Databricks, Snowflake, Redshift, etc.)\nSolid experience in data engineering and pipeline development to support\nmodeled data layers\n5+ years of experience with Databricks and DBT\nExperience with orchestration tools such as Airflow or Dagster\nIn-depth experience with distributed systems such as Spark\nStrong programming skills (Java, Scala, Python) with experience building\nproduction-grade data pipelines\nExperience with AWS cloud services (EC2, EMR, RDS)\nStrong understanding of data standardization, data governance, and data\nquality best practices\nExperience with Git, JIRA, Jenkins, and CI/CD pipelines\nExperience working with cross-functional teams in a dynamic environment\nYou are passionate about data modeling and designing scalable, wellstructured datasets\nYou are equally comfortable implementing pipelines that bring those\nmodels to life\nYou think in terms of data consistency, reusability, and long-term\nmaintainability\nYou value clean design, simplicity, and high-quality engineering practices\nYou have a track record of delivering reliable, well-modeled, production - ready data solutions\n10+ years of experience and a bachelor’s degree in Computer Science, Information Systems, or related field; 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