Aakanksha Deshpande

Data Engineer with 3+ years building production ETL pipelines and lakehouse platforms for a bank and a global consultancy. Hands-on with Azure Data Factory, Azure Databricks, Azure Data Lake Storage Gen2, Delta Lake, PySpark, SQL and Python, including migrating Oracle source data into a Microsoft Fabric Lakehouse for reporting. Led the migration of a 20M+ transactions/day banking data platform to AWS.

MSc Computer Science (Data Analytics), University of Galway; Microsoft Azure Fundamentals (AZ-900) certified.

Data Engineer I at IDFC First Bank (2024-02 – 2025-08)

• Led the migration of the bank’s Account Aggregator data platform to AWS, processing 20M+ daily transactions from 17+ aggregator platforms at 99% data accuracy and improving platform performance by 40%.
• Built real-time PySpark ETL pipelines orchestrated with Airflow, NiFi and Kafka, cutting end-to-end pipeline latency by 50%.
• Organised pipeline outputs into Bronze, Silver and Gold layers with schema enforcement and data versioning, giving downstream teams consistent, reporting-ready datasets.
• Designed data models and validation rules for real-time fraud-detection pipelines, increasing the fraud detection rate by 60%.
• Built Grafana dashboards reporting pipeline health, data quality and anomaly trends to senior management.
• Translated business reporting requirements into data models and pipeline features in Agile sprints with product and analytics stakeholders.

Analyst, Data Engineering at Capgemini (2022-07 – 2024-02)

• Developed ETL/ELT pipelines using Azure Data Factory, Azure Data Lake Storage Gen2, Azure Databricks, PySpark and SQL to migrate Oracle source data into a Microsoft Fabric Lakehouse for analytics and reporting.
• Implemented a Bronze, Silver and Gold Lakehouse architecture with Delta Lake and PySpark to ingest, cleanse, validate and transform datasets, with error handling that flagged data discrepancies before they reached reporting.
• Automated data ingestion from relational databases and REST APIs with Azure Data Factory pipelines, delivering scheduled datasets to business reporting systems.
• Optimised distributed transformations in Azure Databricks, PySpark and SQL, reducing job runtimes by 30%.
• Prepared curated datasets and data models for 8 client reports and data extracts, built to documented business requirements.
• Resolved 50+ production incidents through root-cause analysis, reducing recurring incidents by 25%.

Graduate Teaching Assistant at University of Galway (2025-09 – 2026-05)

• Ran lab sessions and graded assignments for undergraduate Java Programming and Java Web Applications modules.

MSc in Computer Science (Data Analytics) – University of Galway (2025 – 2026)

Bachelor of Engineering in Information Technology – University of Mumbai (2018 – 2022)