Headline

Data Engineer @ Accenture | Building Scalable Data Pipelines & AI Automation | BigQuery · Airflow · Python · SQL

About

I'm a Data Engineer with 2+ years of experience designing and deploying scalable ETL/ELT pipelines, data observability systems, and AI-driven automation frameworks at Accenture. My day-to-day involves building production-grade data pipelines using Python, SQL, BigQuery, and Apache Airflow - optimizing everything from query performance to LLM API costs. I've reduced manual processing time by 70% through end-to-end workflow automation, built data observability layers that improved production data reliability by 20%+, and cut cloud costs by 40% through strategic optimization. What I bring to the table: → Strong SQL and Python skills applied to large-scale data processing → Hands-on experience with BigQuery, Apache Airflow DAGs, and Medallion architecture → Data quality engineering: validation, auditing, drift detection, anomaly monitoring → Cloud platform experience across GCP, AWS, and Azure (all three certified) → Cross-functional collaboration with data analysts, business stakeholders, and engineering teams I'm particularly interested in roles where I can work on complex data infrastructure challenges - building reliable, scalable data platforms that teams can actually trust and use. Currently exploring opportunities in Data Engineering. Let's connect.

Location

Greater Bengaluru Area

AI stack

ChatGPT

Work experience

Data Engineer at Accenture, Feb 2024 - Present · 2 yrs 10 mos, Bengaluru, Karnataka, India, - Built an AI-driven automation framework using Python and Azure OpenAI to execute end-to-end HR workflows, reducing manual processing time by 70% and enabling zero-touch operations - Developed and optimized complex SQL queries in BigQuery for large-scale dataset processing, ensuring data consistency across systems and supporting enterprise data warehouse reporting - Engineered a Data Observability layer with custom Python scripts for auditing, error logging, and data drift detection, improving production data reliability by 20%+ - Reduced LLM API costs by 40% through strategic prompt engineering, token management optimization, and refined experimentation workflows - Automated Apache Airflow DAG alerting and monitoring, cutting incident detection and response time by 50% with improved logging pipelines - Collaborated with Data Analysts and business stakeholders to define metrics, dimensions, and dashboard requirements for self-serve data consumption - Identified and resolved SQL and pipeline bottlenecks in BigQuery, improving query performance and resource utilization across mission-critical workflows

IT Intern at Johnson Controls, Jan 2023 - Jul 2023 · 7 mos, Bengaluru, Karnataka, India, - Researched carbon capture technologies and their integration with current infrastructure. - Proposed a data-backed model that lowered carbon footprint and generated new revenue opportunities. - Developed a SharePoint site to improve stakeholder collaboration and reporting workflow

Education

Bachelor of Engineering - BE, Computer Science, Sri Venkateshwara College of Engineering, BANGALORE