Pull/ingest data from different sources, transform and stitch, and wrangle it for advanced analytics activities.
Design, implement, and deploy data loaders to load data into the Engineering Sandbox.
Leverage data best practices and tools and assist ML engineer in pulling, filtering, tagging, joining, parsing, and normalizing data sets for use.
Provide input to ML engineer/cloud engineer for the design and implementation of data management and/or architecture solutions.
Develop & deploy azure databricks in a cloud environment using Azure Cloud services
ETL design, development, and deployment to Cloud Service
Interact with Onshore, understand their business goals, contribute to the delivery of the workstreams
Design and optimize model codes for faster execution.
Must have:
3 to 7 years of Experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases, NoSQL, and data warehouse solutions
Extensive hands-on experience implementing data migration and data processing using Azure services: Databricks, ADLS, Azure Data Factory, Azure Functions, Synapse/DW, Azure SQL DB, etc.
Hands on experience in programming like python/pyspark
Need to have good knowledge on DWH concepts and implementation knowledge on Snowflake
Well versed in DevOps and CI/CD deployments
Must have hands on experience in SQL and procedural SQL languages.
Strong analytical skills and enjoys solving complex technical problems.
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.