About the Role
Candidate is expected to demonstrate extensive knowledge and/or a proven record of success in the
following areas:
· Should have minimum 6 years hand on experience building advanced Data warehousing solutions on
leading cloud platforms.
· Should have minimum 3-5 years of Operate/Managed Services/Production Support Experience
· Should have extensive experience in developing scalable, repeatable, and secure
data structures and pipelines to ingest, store, collect, standardize, and integrate data that for
downstream consumption like Business Intelligence systems, Analytics modeling, Data scientists etc.
· Designing and implementing data pipelines to extract, transform, and load (ETL) data from various sources
into data storage systems, such as data warehouses or data lakes.
· Should have experience in building efficient ETL/ELT processes using industry leading tools like AWS, AWS
GLUE, AWS Lambda, AWS DMS, PySpark, SQL, Python, DBT, Prefect, Snowflake, etc.
· Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in AWS.
· Work together with data scientists and analysts to understand the needs for data and create effective data
workflows.
· Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability
of the data.
· Improve the scalability, efficiency, and cost-effectiveness of data pipelines.
· Monitoring and troubleshooting data pipelines and resolving issues related to data processing,
transformation, or storage.
· Implementing and maintaining data security and privacy measures, including access controls and
encryption, to protect sensitive data
· Advanced working SQL knowledge and experience working with relational databases, query authoring
(SQL) as well as working familiarity with a variety of databases
· Should have experience in Building and maintaining Data Governance solutions (Data Quality, Metadata
management, Lineage, Master Data Management and Data security) using industry leading tools
· Scaling and optimizing schema and performance tuning SQL and ETL pipelines in data lake and data
warehouse environments.
· Should have Hands-on experience with Data analytics tools like Informatica, Collibra, Hadoop, Spark,
Snowflake etc.
· Should have Experience of ITIL processes like Incident management, Problem Management, Knowledge
management, Release management, Data DevOps etc.
· Should have Strong communication, problem solving, quantitative and analytical abilities.
Requirements
Work Experience : 3 years (US)
Minimum Degree Required (BQ) : Bachelor's degree Preferred Knowledge/Skills : AWS Cloud Engineer, AWS certification