HEMA SAINI

• Leading end-to-end delivery of multiple data engineering projects—covering both real-time (Autoloader-based) and batch processing—from requirement gathering and design to development, deployment, and ongoing maintenance.
• Built scalable data pipelines using Azure Databricks, Autoloader, PySpark, SQL, and Delta Lake to transform and serve telemetry and operational data.
• Configured and managed Azure IoT infrastructure including IoT Hub and Azure Functions for ingesting and routing industrial sensor data.
• Implemented ingestion and transformation logic using Databricks Autoloader with Delta Lake merge strategies, enabling schema evolution, late-arriving data support, and high-volume processing.
• Designed and implemented CI/CD pipelines, including YAML-based deployment workflows in Azure DevOps to automate build, test, and release processes for both data pipelines and machine learning models developed by the data science team.
• Led and supported two junior data engineers, providing technical guidance, overseeing task delivery, and fostering their professional development through regular feedback and mentorship.

• Led data engineering initiatives to modernize Prudential’s finance data stack by migrating ETL jobs and critical data assets—including Unix shell scripts, Informatica workflows, and T-SQL procedures—from Unix-based on-premises systems to Azure Data Factory and Databricks.
• Designed and implemented scalable pipelines using ADF, PySpark, and Azure Databricks, incorporating Spark SQL to transform and deliver investment policy, claims, and customer transaction data.
• Utilized DevOps practices through Azure DevOps and GitHub to manage CI/CD pipelines, automate job deployments, and ensure version control.
• Created reusable PySpark modules for data quality validation, schema checks, and exception handling, improving operational resilience across finance pipelines.
• Partnered with finance and actuarial teams to ensure cloud pipelines met regulatory standards and financial reporting needs (e.g., MAS compliance).
• Mentored junior engineers and promoted engineering best practices, improving delivery speed and code maintainability.

Client Project: OCBC Bank – Customer Data Platform & Compliance Pipelines

• Designed and developed PySpark pipelines to ingest and transform customer transaction and demographic data into Hive, aligning with Teradata FSLDM-based data models.
• Utilized Spark SQL, HiveQL, and PostgreSQL to process large-scale JSON and structured files for AML, KYC, and regulatory reporting.
• Validated and enriched data using Python, Pandas, NumPy, and PostgreSQL, especially for Excel-based customer onboarding data.
• Migrated and re-engineered legacy Hive/SQL scripts into PySpark, improving scalability, modularity, and maintainability.
• Collaborated with business users on SIT, UAT, and production rollouts, documenting transformation logic aligned with FSLDM subject areas.

Client Project: DBS Bank – Data Warehouse Migration & Regulatory Reporting

• Migrated batch jobs from AIX to Hadoop (Linux), integrating legacy financial data into HDFS and Hive, maintaining FSLDM consistency across financial and risk domains.
• Built PySpark and SQL-based Python modules for data cleansing and historical tracking, enabling efficient daily file ingestion and validation.
• Optimized Teradata SQL queries for performance and restructured job scheduling using Control-M to ensure alignment with SLAs and dependency chains.
• Worked with data architects to map Teradata entities to Hive structures, preserving reporting lineage and ensuring compliance.
• Developed data workflows for a contextual marketing initiative, enabling targeted offers based on customer transaction and spend behavior.

• Designed, developed, and enhanced ETL processes using Informatica PowerCenter, leveraging SQL and PL/SQL to support transformation logic for structured and unstructured insurance data.
• Developed integration workflows for Claims Processing Engine and HIPAA-compliant formats (834, 275, 277) using Informatica B2B Data Transformation.
• Built ingestion and transformation workflows using Unix shell scripting, SQL*Loader, and SQL, handling flat files and Excel-based source systems.
• Created and validated reports using Excel for insurance web services; managed debugging through session logs and error tracking.
• Maintained comprehensive documentation including ETL specs, unit tests, and migration checklists to support integration for Medicaid and Medicare compliance.