About H.E. Services: At H.E. Services vibrant tech Center in Hyderabad, you will have the opportunity to contribute to technology innovation for Holman Automotive, a leading American fleet management and automotive services company. Our goal is to continue investing in people, processes, and facilities to ensure expansion in a way that allows us to support our customers and develop new tech solutions. Holman has come a long way during its first 100 years in business. The automotive markets Holman serves include fleet management and leasing; vehicle fabrication and up fitting; component manufacturing and productivity solutions; powertrain distribution and logistics services; commercial and personal insurance and risk management; and retail automotive sales as one of the largest privately owned dealership groups in the United States. Join us and be part of a team that's transforming the way Holman operates, creating a more efficient, data-driven, and customer-centric future. Roles & Responsibilities: Design, develop, and maintain data pipelines using Databricks , Spark , and other Azure cloud technologies. Optimize data pipelines for performance, scalability, and reliability, ensuring high speed and availability of data warehouse performance. Develop and maintain ETL processes using Databricks and Azure Data Factory for real-time or trigger-based data replication. Ensure data quality and integrity throughout the data lifecycle, implementing new data validation methods and analysis tools. Collaborate with data scientists, analysts, and stakeholders to understand and meet their data needs. Troubleshoot and resolve data-related issues, providing root cause analysis and recommendations. Manage a centralized data warehouse in Azure SQL to create a single source of truth for organizational data, ensuring compliance with data governance and security policies. Document data pipeline specifications, requirements, and enhancements, effectively communicating with the team and management. Leverage AI/ML capabilities to create innovative data science products. Champion and maintain testing suites, code reviews, and CI/CD processes. Must Have: Strong knowledge of Databricks architecture and tools. Proficient in SQL , Python , and PySpark for querying databases and data processing. Experience with Azure Data Lake Storage (ADLS) , Blob Storage , and Azure SQL . Deep understanding of distributed computing and Spark for data processing. Experience with data integration and ETL tools, including Azure Data Factory. Advanced-level knowledge and practice of: Data warehouse and data lake concepts and architectures. Optimizing performance of databases and servers. Managing infrastructure for storage and compute resources. Writing unit tests and scripts. Git, GitHub, and CI/CD practices. Good to Have: Experience with big data technologies, such as Kafka , Hadoop , and Hive . Familiarity with Azure Databricks Medallion Architecture with DLT and Iceberg. Experience with semantic layers and reporting tools like Power BI . Relevant Work Experience: 5+ years of experience as a Data Engineer, ETL Developer, or similar role, with a focus on Databricks and Spark. Experience working on internal, business-facing teams. Familiarity with agile development environments. Education and Training: Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent work experience.
Job Title
Senior Analyst - Data Platform