{"schemaVersion":"jobsearcher.job.v1","id":"61d78e04df9398c2d25f3803","url":"https://jobsearcher.com/jobs/61d78e04df9398c2d25f3803","canonicalUrl":"https://jobsearcher.com/jobs/61d78e04df9398c2d25f3803","title":"Hadoop Hive Python Developer","description":"Job DescriptionMust Have Technical/Functional SkillsPrimary skills: Hadoop, Hive, Python, PySpark, Apache Kafka, Hadoop Ecosystem, Hive, Databricks Lakehouse Architecture, Delta Lake, Bronze/Silver/Gold Data Modeling, Big Data ETL Pipeline Development, SQL, Real-time Data Ingestion Frameworks, Data Governance & Cataloging, CI/CD Tools – Git, Jenkins, Bitbucket, Workflow Orchestration, and Cloud & On-Prem Big Data Platforms.Experience: Minimum 9+ yearsRoles & ResponsibilitiesSeeking a Senior Big Data Engineer with 9-14 years of experience specializing in Hadoop, Python, Hive PySpark, Kafka, and strong experience designing data solutions for large-scale financial systems.In addition, the candidate must possess advanced expertise in Databricks Lakehouse architecture, particularly around Bronze/Silver/Gold layer data modeling, Delta Lake optimizations, and building reliable, scalable pipelines for regulatory, risk, trading, and analytics workloads.This role focuses on delivering highly performant, well-governed data platforms that support the bank’s mission-critical global markets functions.Key ResponsibilitiesBig Data Platform Engineering Design, develop, and optimize PySpark-based ETL pipelines running on on‑prem Hadoop clusters and cloud environments. Build high‑volume ingestion frameworks using Kafka for real-time and near-real-time trading and market data. Develop, tune, and manage Hadoop ecosystem components—HDFS, YARN, MapReduce, Tez, Oozie/Airflow. Build high-performance, optimized Hive data models for regulatory reporting, trade lifecycle, and market risk processing.Databricks Lakehouse & Delta Framework Architect and implement Bronze/Silver/Gold layer modeling patterns within the Databricks Lakehouse. Apply Delta Lake best practices including:optimized file managementZ-OrderingDelta Change Data Feed (CDF)schema evolution & enforcementACID transaction handling Build reusable frameworks for ingestion, cleansing, transformation, and consumption of data across Lakehouse layers. Enable governance, lineage, and auditability using Unity Catalog or equivalent cataloging tools.Collaboration, Leadership & Delivery Collaborate closely with quants, product owners, architects, risk tech, and business users. Participate in agile ceremonies — sprint planning, refinement, design reviews. Mentor junior engineers and contribute to building strong engineering practices across tech teams.Required Skills & Experience 9-14 years of hands-on experience in Big Data engineering. Expert skills in:PySpark — dataframe optimizations, partitioning, broadcast strategies, distributed computing.Kafka — producer/consumer design, schema registry, streaming ETLs.Hadoop ecosystem — HDFS, YARN, MapReduce/Tez, Oozie/Airflow.Hive — advanced query tuning, TEZ optimization, partition/bucket management. Extensive hands-on experience with Databricks Lakehouse, including:Bronze/Silver/Gold layer modelingDelta Lake optimizationsData quality frameworks on LakehouseStructured & unstructured data handling Experience in Global Markets, Risk, Treasury, Trade Surveillance, or Regulatory Reporting. Strong SQL knowledge with experience working on massive datasets (TB/PB scale). Experience with CI/CD practices — Git, Jenkins, Bitbucket, build pipelines.TCS Employee Benefits SummaryDiscretionary Annual Incentive.Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.Family Support: Maternal & Parental Leaves.Insurance Options: Auto & Home Insurance, Identity Theft Protection.Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.Time Off: Vacation, Time Off, Sick Leave & Holidays.Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.Salary Range: $110,000-$125,000 a yearQualifications: BACHELOR OF COMPUTER SCIENCE","company":"Tata Consultancy Services","rawCompany":"tata consultancy services","city":"Charlotte","state":"NC","isRemote":false,"isActive":false,"createdAt":"2026-08-29T09:15:41.288Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Hadoop Hive Python Developer","description":"Job DescriptionMust Have Technical/Functional SkillsPrimary skills: Hadoop, Hive, Python, PySpark, Apache Kafka, Hadoop Ecosystem, Hive, Databricks Lakehouse Architecture, Delta Lake, Bronze/Silver/Gold Data Modeling, Big Data ETL Pipeline Development, SQL, Real-time Data Ingestion Frameworks, Data Governance & Cataloging, CI/CD Tools – Git, Jenkins, Bitbucket, Workflow Orchestration, and Cloud & On-Prem Big Data Platforms.Experience: Minimum 9+ yearsRoles & ResponsibilitiesSeeking a Senior Big Data Engineer with 9-14 years of experience specializing in Hadoop, Python, Hive PySpark, Kafka, and strong experience designing data solutions for large-scale financial systems.In addition, the candidate must possess advanced expertise in Databricks Lakehouse architecture, particularly around Bronze/Silver/Gold layer data modeling, Delta Lake optimizations, and building reliable, scalable pipelines for regulatory, risk, trading, and analytics workloads.This role focuses on delivering highly performant, well-governed data platforms that support the bank’s mission-critical global markets functions.Key ResponsibilitiesBig Data Platform Engineering Design, develop, and optimize PySpark-based ETL pipelines running on on‑prem Hadoop clusters and cloud environments. Build high‑volume ingestion frameworks using Kafka for real-time and near-real-time trading and market data. Develop, tune, and manage Hadoop ecosystem components—HDFS, YARN, MapReduce, Tez, Oozie/Airflow. Build high-performance, optimized Hive data models for regulatory reporting, trade lifecycle, and market risk processing.Databricks Lakehouse & Delta Framework Architect and implement Bronze/Silver/Gold layer modeling patterns within the Databricks Lakehouse. Apply Delta Lake best practices including:optimized file managementZ-OrderingDelta Change Data Feed (CDF)schema evolution & enforcementACID transaction handling Build reusable frameworks for ingestion, cleansing, transformation, and consumption of data across Lakehouse layers. Enable governance, lineage, and auditability using Unity Catalog or equivalent cataloging tools.Collaboration, Leadership & Delivery Collaborate closely with quants, product owners, architects, risk tech, and business users. Participate in agile ceremonies — sprint planning, refinement, design reviews. Mentor junior engineers and contribute to building strong engineering practices across tech teams.Required Skills & Experience 9-14 years of hands-on experience in Big Data engineering. Expert skills in:PySpark — dataframe optimizations, partitioning, broadcast strategies, distributed computing.Kafka — producer/consumer design, schema registry, streaming ETLs.Hadoop ecosystem — HDFS, YARN, MapReduce/Tez, Oozie/Airflow.Hive — advanced query tuning, TEZ optimization, partition/bucket management. Extensive hands-on experience with Databricks Lakehouse, including:Bronze/Silver/Gold layer modelingDelta Lake optimizationsData quality frameworks on LakehouseStructured & unstructured data handling Experience in Global Markets, Risk, Treasury, Trade Surveillance, or Regulatory Reporting. Strong SQL knowledge with experience working on massive datasets (TB/PB scale). Experience with CI/CD practices — Git, Jenkins, Bitbucket, build pipelines.TCS Employee Benefits SummaryDiscretionary Annual Incentive.Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.Family Support: Maternal & Parental Leaves.Insurance Options: Auto & Home Insurance, Identity Theft Protection.Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.Time Off: Vacation, Time Off, Sick Leave & Holidays.Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.Salary Range: $110,000-$125,000 a yearQualifications: BACHELOR OF COMPUTER SCIENCE","datePosted":"2026-08-29T09:15:41.288Z","dateModified":"2026-08-29T09:15:41.288Z","hiringOrganization":{"@type":"Organization","name":"Tata Consultancy Services","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Charlotte","addressRegion":"NC","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"61d78e04df9398c2d25f3803"},"url":"https://jobsearcher.com/jobs/61d78e04df9398c2d25f3803"}}