EY - GDS Consulting - AI and DATA - Snowflake - Senior

Trivandrum 4 Years Exp Posted 2d ago

Develop & deploy big data pipelines in a cloud environment using Snowflake cloud DW
ETL design, development and migration of existing on-prem ETL routines to Cloud Service
Interact with senior leaders, understand their business goals, contribute to the delivery of the workstreams
Design and optimize model codes for faster execution

Skills and attributes for success

Hands on developer in the field of data warehousing, ETL
Hands on development experience in Snowflake.
Experience in Snowflake data modelling - roles, schema, databases and security policies.
Hands on development experience with Tasks, Streams and stages on Snowflake
Experience in Data Integration using third-party tools like Matillion / Palantir / Informatica / DBT etc
Experience in Snowflake advanced concepts like setting up resource monitors and performance tuning would be preferable
Develop data pipelines to perform batch and Real - Time/Stream analytics on structured and unstructured data.
Data Ingress, Egress, Querying using Kafka, NiFi
Deep understanding of AWS S3, Lambda, EMR, Glue
Data processing patterns, distributed computing and in building applications for real-time and batch analytics.
Handling large data sets and perform data wrangling, analysis, etc., using various SQL & NoSQL database technologies, and programming languages such as Java/Scala/Python
Good understanding of different file format (ORC, Parquet, AVRO) to optimize queries/processing and compression techniques
Have knowledge and skills in DevOps and containerization. Preferable – having deployment knowledge

To qualify for the role, you must have

Be a computer science graduate or equivalent with 4-7 years of industry experience
Have working experience in an Agile base delivery methodology (Preferable)
Flexible and proactive/self-motivated working style with strong personal ownership of problem resolution.
Excellent communicator (written and verbal formal and informal).
Participate in all aspects of Big Data solution delivery life cycle including analysis, design, development, testing, production deployment, and support.