Pranay Sarode

Data Engineer with 3+ years of core data engineering experience across financial services and telecommunications, with earlier analytics/BI experience in fintech. Hands-on in Python, SQL, PySpark, Apache Spark, Azure Databricks, Azure Data Lake, Azure Data Factory, AWS S3, SSIS, data quality, ETL/ELT, and CI/CD. Experienced in building batch ingestion and transformation workflows, validating and reconciling enterprise datasets, optimizing SQL/Spark processing, and delivering analytical data products to business stakeholders.

Strong focus on reliability, traceability, documentation, and Agile collaboration.

Data Engineer at Infosys Limited (2021-03 – 2024-11)

Project 1 - Capital Group Portfolio Analytics | Financial Services (Dec 2022 - Nov 2024) Project 2 - Broadband Customer Churn Analytics | Telecommunications (Mar 2021 - Nov 2022)

• Built PySpark, Python, and SQL ETL workflows to ingest, cleanse, transform, and reconcile high-volume investment datasets across CSV, JSON, Parquet, Azure Data Lake, and AWS S3.
• Implemented automated data-quality controls covering schema validation, null checks, business-rule validation, and source-to-target reconciliation; supported quality-controlled and compliance-sensitive deliverables.
• Optimized SQL Server queries and analytical logic for NAV, risk, fund performance, and KPI reporting across large investment datasets.
• Supported migration/modernization of legacy data sources into a centralized Azure analytics platform and used Azure Databricks for distributed processing.
• Automated reporting/deployment activities with Python, Git, and Jenkins; participated in sprint planning, stand-ups, code reviews, architecture discussions, and global stakeholder reviews.
• Built PySpark ETL workflows for high-volume telecom usage, demographic, CSV, Parquet, JSON, and log data; performed cleansing, transformation, feature engineering, and preparation for analytics/ML.
• Developed advanced SQL transformations using joins, CTEs, and window functions to derive churn features and customer behavior indicators.
• Implemented ETL testing for schema checks, null handling, reconciliation, and data-quality validation across data-lake and warehouse layers.
• Used SSIS for scheduled batch data movement and processing; automated recurring reporting with Python/Excel VBA and supported dev/test/prod delivery through CI/CD practices.
• Developed churn analysis/predictive models and Power BI dashboards to expose churn-risk segments and KPIs; documented model/pipeline behavior and presented findings to stakeholders.

MIS Executive / Data Analyst at Mphasis Limited (2019-05 – 2021-02)

Project 3 - Klarna US Customer Behavior & Fintech Analytics

• Analyzed historical transaction data using SQL and Python to derive purchase frequency, spend behavior, payment preferences, cohort trends, and customer segments.
• Built PySpark ETL workflows to ingest, cleanse, and transform structured and semi-structured data from AWS S3/Azure Blob Storage into centralized analytical datasets/warehouse layers.
• Applied schema checks, null handling, record reconciliation, and pipeline-quality checks to improve trust in downstream reporting datasets.
• Developed predictive customer-behavior analysis with Python/Scikit-learn and created Power BI dashboards using DAX for AOV, conversion, cohort behavior, and anomaly monitoring.
• Presented data-driven findings to marketing/product stakeholders to support customer engagement, promotion, and retention decisions.

Senior Associate, MIS & Reporting at Wipro Limited (2016-12 – 2019-02)

• Automated MIS/Power BI reporting; SQL/Python trend analysis.

Assistant Resident Engineer, Network Support at Dhruva Enterprises (2013-08 – 2016-05)

• Network monitoring, troubleshooting, RCA, and technical documentation.

Bachelor of Arts in Economics – University of Pune