> Markdown version of [/jobs/ext/2000130-etl-developer](https://www.wearedevelopers.com/jobs/ext/2000130-etl-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ETL Developer - **Company:** TCS - Tata Consultancy Services - **Location:** Plano, TX, United States - **Contract:** Permanent contract - **Skills:** Airflow, Big Data, Continuous Integration, Data Governance, Extract Transform Load (ETL), Data Systems, Apache Hadoop, Hadoop Distributed File System, MapReduce, Apache Hive, Apache Oozie, Performance Tuning, Query Optimization, Standard Sql, Unstructured Data, Cloud Platform System, Apache Yarn, Git, Data Lakes, Pyspark, Real Time Data, Apache Kafka, Bitbucket, Data Management, Tez (Software), Data Pipelines, Jenkins, Databricks - **Published:** August 9, 2026 - **Apply:** https://us.experteer.com/career/view-jobs/etl-developer-plano-tx-usa-58862790 ## About the Role Jenkins, and implement Bronze/Silver/Gold layer modeling in Databricks Lakehouse * Apply Delta Lake best practices (file management, Z-Ordering, CDF, schema evolution, ACID) * Create reusable ingestion, cleansing, transformation, and consumption frameworks across Lakehouse layers * Enable governance, lineage, and auditability using cataloging tools (Unity Catalog or equivalent) * Collaborate with quants, product owners, risk tech, and business users; participate in agile ceremonies * Mentor junior engineers and promote strong engineering practices across teams Tasks * 10-13 years of hands-on Big Data engineering experience * Expert in PySpark (optimizations, partitioning, broadcasting) * Expert in Kafka (producer/consumer design, schema registry, streaming ETLs) * Strong Hadoop ecosystem knowledge (HDFS, YARN, MapReduce/Tez, Oozie/Airflow) * Advanced Hive skills (query tuning, TEZ, partitioning) * Extensive Databricks Lakehouse experience (Bronze/Silver/Gold, Delta Lake optimizations) * Experience with data quality frameworks on Lakehouse and handling structured/unstructured data * Experience in Global Markets, Risk, Treasury, Trade Surveillance, or Regulatory Reporting * Strong SQL on TB/PB-scale datasets * Experience with CI/CD practices (Git, Jenkins, Bitbucket) * Familiarity with governance/catalog tools for lineage and auditability * Experience with on-prem and cloud big data platforms Key requirements * Discretionary annual incentive * Medical coverage * Parental leaves * Commuter benefits * Certification & training reimbursement * Vacation & holidays ## Description Experteer Overview In this role you will design and optimize large-scale data platforms for global markets. You will build real-time and batch data pipelines, focusing on PySpark, Kafka, and Hadoop ecosystems, while advancing Databricks Lakehouse architectures. You will work closely with quants, risk teams, and product owners to deliver governed, high-performance data solutions for regulatory, trading, and analytics workloads. The opportunity centers on shaping scalable, compliant data platforms that support mission-critical financial functions. You will mentor engineers and contribute to strong engineering practices. Compensation / Benefits * Design, develop, and optimize PySpark ETL pipelines on on-prem Hadoop clusters and cloud environments * Build high-volume ingestion frameworks using Kafka for real-time data * Tuning and managing Hadoop components: HDFS, YARN, MapReduce/Tez, Oozie/Airflow * Develop high-performance Hive data models for regulatory reporting and risk processing * Architect and implement Bronze/Silver/Gold layer modeling in Databricks Lakehouse * Apply Delta Lake best practices (file management, Z-Ordering, CDF, schema evolution, ACID) * Create reusable ingestion, cleansing, transformation, and consumption frameworks across Lakehouse layers * Enable governance, lineage, and auditability using cataloging tools (Unity Catalog or equivalent) * Collaborate with quants, product owners, risk tech, and business users; participate in agile ceremonies * Mentor junior engineers and promote strong engineering practices across teams Tasks * 10-13 years of hands-on Big Data engineering experience * Expert in PySpark (optimizations, partitioning, broadcasting) * Expert in Kafka (producer/consumer design, schema registry, streaming ETLs) * Strong Hadoop ecosystem knowledge (HDFS, YARN, MapReduce/Tez, Oozie/Airflow) * Advanced Hive skills (query tuning, TEZ, partitioning) * Extensive Databricks Lakehouse experience (Bronze/Silver/Gold, Delta Lake optimizations) * Experience with data quality frameworks on Lakehouse and handling structured/unstructured data * Experience in Global Markets, Risk, Treasury, Trade Surveillance, or Regulatory Reporting * Strong SQL on TB/PB-scale datasets * Experience with CI/CD practices (Git, Jenkins, Bitbucket) * Familiarity with governance/catalog tools for lineage and auditability * Experience with on-prem and cloud big data platforms Key requirements * Discretionary annual incentive * Medical coverage * Parental leaves * Commuter benefits * Certification & training reimbursement * Vacation & holidays ## Related Videos - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [The Road to MLOps: How Verivox Transitioned to AWS](https://www.wearedevelopers.com/videos/1050-the-road-to-mlops-how-verivox-transitioned-to-aws) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Our GitOps approach for deploying an Identity Provider and an API Gateway in a SaaS company](https://www.wearedevelopers.com/videos/776-our-gitops-approach-for-deploying-an-identity-provider-and-an-api-gateway-in-a-saas-company) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence)