Saurav Chaubal

Data Engineer at Accenture with 3.9 years of experience building and optimizing cloud-based data platforms using Databricks, Snowflake, PySpark, Airflow, and AWS. Skilled in developing scalable batch and streaming pipelines, implementing CI/CD and Infrastructure as Code practices, and driving data reliability through observability and quality frameworks. Delivered 40% performance improvements while supporting enterprise-scale workloads with 99.9% SLA adherence.

Software Engineer at Accenture Solutions Pvt. Ltd. (2022-12 – Present)

• Built and maintained batch and near-real-time ETL/ELT pipelines using Databricks, PySpark, Snowflake, and Apache Airflow, processing 2M+ records daily with 99%+ SLA adherence.

• Developed reusable PySpark with CDC ingestion frameworks for API and enterprise sources, reducing pipeline runtime by 32% and improving downstream data availability from ~90 minutes to under 35 minutes.

• Automated Databricks job/notebook deployments using Git-based CI/CD, reducing release turnaround by 40% and minimizing manual deployment errors across environments.

• Improved reliability across 12+ pipelines through data quality checks, reconciliation, lineage, monitoring, and exception handling, cutting recurring data-quality incidents by nearly a third.

• Optimized SQL and PL/SQL transformations across 30M+ record datasets, achieving 35 - 45% faster query execution through improved joins, partitioning, and transformation logic.

• Supported legacy workload migration to Databricks/Snowflake, collaborating with DBAs, analysts, and business teams in a SAFe Agile environment to deliver scalable data solutions and reduce batch processing time by 30%.

• Analysed plant operational data using Python and Excel. Delivered insights that improved heat exchanger efficiency by 15%.

Executive MBA in Data Science and AI – K.J. Somaiya Institute of Management, Mumbai (2026-07)

B.Tech in Mechanical Engineering – Vellore Institute of Technology, Vellore (2022-05)