Headline

Data Engineer | Building Scalable ETL Pipelines on Azure & Databricks | PySpark · ADF · Delta Lake | Ex-Capgemini Rising Star | M.E. CS @ Thapar

About

I'm a postgraduate student pursuing my Master of Engineering in Computer Science at Thapar Institute of Engineering and Technology (GPA: 8.3/10), building on a strong foundation from my undergraduate degree at Chandigarh University. My academic journey has been shaped by a deep interest in distributed systems, cloud-native data architecture, and applied AI — interests that have carried naturally into my professional work. Alongside my studies, I hold a Google Advanced Data Analytics Certificate and an Alteryx Core Certification, keeping my skills current with industry standards. At Capgemini, where I progressed from Data Analyst Trainee to Senior Analyst over 3 years 1 month, I owned two end-to-end client engagements in the data warehouse and sports-data integration space. A highlight was cutting a legacy pipeline's historical-load runtime by 60% — from 10–11 hours to 3–4 hours — by tuning Synapse Dedicated SQL Pool DWUs and rebuilding incremental ADF pipelines on ADLS Gen2. I also built Power BI dashboards used daily by 200+ internal users and received the Rising Star Award for top-tier delivery performance. More recently, through my academic internship at Revclerx AI Solutions, I worked on a live multi-agent AI platform (RAG, agentic workflows, GPT-4o), where I raised RAG retrieval accuracy by 20% through chunking, re-ranking, and vector indexing tuning. Across both roles, I've worked across Azure, Databricks, PySpark, Delta Lake, ADF, dbt, and Power BI — with a consistent focus on pipeline reliability, data quality, and measurable business outcomes. I'm looking to join a high-impact data engineering team at a company where data infrastructure is taken seriously — one that works at scale and values clean, reliable pipelines over quick fixes. My goal is to grow into a senior or lead data engineering role where I can own architecture decisions, mentor junior engineers, and bridge the gap between raw data and real business insight. I'm particularly drawn to organisations working at the intersection of cloud data platforms and applied AI. amanjot.k.sahni@gmail.com 🔗 linkedin.com/in/amanjotsahni github.com/amanjotsahni +91 9877471845

Location

Punjab

AI stack

antigravity

codex

claudecode

Work experience

AI / Agentic Systems Engineer Intern at RevClerx Pvt Ltd, Jun 2025 - Apr 2026 · 11 mos, On-site, Worked on validating and testing a multi-agent AI platform supporting enterprise workflows, RAG-based knowledge retrieval, and conversational agents. Designed AI testing frameworks covering prompt engineering, intent detection, context preservation, and multi-step agent execution across enterprise environments. Evaluated RAG pipelines for grounding accuracy, hallucination detection, and document permission enforcement across enterprise knowledge sources. Built adversarial prompt test suites and Langfuse observability workflows to detect prompt injection risks, trace agent execution paths, and debug latency and routing failures.

Senior Analyst at Capgemini, Jan 2023 - Feb 2024 · 1 yr 2 mos, India, Led data engineering contributions on an enterprise MDW migration initiative, migrating legacy SQL Server and SSIS pipelines to an Azure-based cloud data platform. Built and managed ingestion workflows using Azure Data Factory to consolidate data from multiple enterprise sources into ADLS storage layers for downstream processing. Implemented data preprocessing and validation workflows in Databricks and SQL, handling incremental data loads three times daily — performing schema validation, data cleansing, and resolving production issues including datatype mismatches and length constraint failures. Developed data warehouse transformations in Azure Synapse Analytics, creating staging pipelines, fact and dimension tables, and optimized warehouse workloads — reducing a 10–11 hour historical load to approximately 3–4 hours. Supported reliable Power BI reporting dashboards for business stakeholders.

Analyst at Capgemini, Jun 2021 - Dec 2022 · 1 yr 7 mos, Mumbai, Maharashtra, India, Developed scalable ETL pipelines using Python, SQL, and Azure Data Factory to ingest and transform enterprise datasets across multiple client initiatives. Contributed to SportsEngine data integration project, designing SQL transformations and ingestion workflows across Azure data environments. Supported Airbnb analytics workloads — building data validation frameworks, reporting pipelines, and analytical dashboards for business insights. Gained hands-on experience across the Azure data ecosystem including Azure Data Factory, Azure Synapse Analytics, and SQL-based transformations at enterprise scale.

Intern at Capgemini, Feb 2021 - Jun 2021 · 5 mos

Trainee at TCIL-IT Chandigarh, May 2019 - Jun 2019 · 2 mos, Chandigarh, India, 6-week training on web development in python.

Education

Master of Engineering - MEng, Computer science and engineering, Thapar Institute of Engineering & Technology

Bachelor of Engineering, Computer Science engineering, CHANDIGARH UNIVERSITY