Role Description:
• Design, develop, and maintain scalable Big Data solutions using Spark, Hive, and distributed data processing frameworks to support enterprise analytics and reporting.
• Build and optimize data pipelines for ingesting, transforming, and integrating structured and unstructured data from multiple enterprise sources.
• Develop and manage cloud-native data platforms leveraging AWS services such as S3, Glue, EMR, Lambda, Redshift, and related technologies.
• Implement and support Snowflake-based data warehousing solutions, including schema design, performance tuning, data shar ing, and workload optimization.
• Create and maintain logical and physical data models, ensuring scalability, data integrity, consistency, and business alignment.
• Collaborate with Data Architects, Business Analysts, Data Scientists, and business stakeholders to translate analytical and reporting requirements into technical solutions.
• Design and optimize ETLELT processes to improve data quality, processing efficiency, and operational performance.
• Ensure adherence to data governance, security, compliance, and privacy standards across the enterprise data ecosystem.
• Perform data profiling, validation, reconciliation, and root cause analysis to address data quality and production issues.
• Support advanced analytics, machine learning, and business intelligence initiatives by delivering trusted, high-quality data assets.
• Lead performance optimization activities across Spark jobs, Hive queries, Snowflake workloads, and AWS data services to improve scalability and cost efficiency.
• Mentor junior engineers and contribute to engineering standards, CICD practices, code reviews, documentation, and best practices for data engineering excellence.

Thank you for your interest in TCS. Candidates that meet the qualifications for this position will be contacted within a 2-week period. We invite you to continue to apply for other opportunities that match your profile.