Extraction of structured, unstructured data coming from streaming and batch sources and refining/cleansing data to make it available on legacy database systems or cloud systems, to data scientists and business users for exploration and analysis

Extracting, processing, transforming, and loading data techniques into various relational, non-relational, noSQL, big data systems and/or cloud storages, depending on data availability, volume, velocity, type of data

An efficient and smart approach for migrating business data to/from on-prem legacy systems into cloud storage infrastructure or new target platforms

Building production-grade replayable and independent data workflow pipelines to move, transform and store data using various legacy, Big Data and / or cloud orchestration and data management pipeline tools and techniques like DF, Databricks, Synapse, Informatica, etc., to process data in batch and real time

Expertise in legacy and cloud-based deployment services for developing efficient production build and release pipelines based on infrastructure-as-code artifacts, reference / application data, database objects (schema definitions, functions, stored procedures, etc.), data pipeline definitions and data validation and transformation logics

Expertise in implementing real-time and batch data processing systems across distributed environments based on mobile, web hosting and cloud services