Description

You will build and maintain complex data pipelines and integration services across cloud and on-premise environments.

Responsibilities

• Provide data integration services for batch and real-time data movement across data warehouses, data lakes, and data marts.
• Design, build, and manage the end-to-end lifecycle for data migration, integration, and data services-oriented solutions.
• Perform data analysis to ensure accuracy and efficiency, communicating results to technical and operational teams.
• Test data integration and warehouse solutions to ensure completeness and adherence to functional and service level requirements.
• Optimize data flows and identify process inefficiencies to improve processing capabilities.

Required Skills

• 8+ years of experience creating and maintaining ETL processes and architecting complex data pipelines.
• 3+ years of experience with Snowflake and AWS Redshift.
• 5+ years of experience with ETL and data ingestion tools including Informatica IICS, AWS Glue, or SAP BODS.
• 5+ years of experience designing and building data pipeline/ETL frameworks with cloud-based technologies.
• Proficiency in ANSI-SQL, Python, Scala, and/or Java.
• 3+ years of experience with AWS services including Lake Formation, Glue, S3, Lambda, and DynamoDB.
• 3+ years of experience with Big Data technologies such as Hadoop, Hive, Spark, No-SQL, Kafka, and APIs.
• 1+ years of experience designing data privacy constructs for tokenization, encryption, and access controls on public cloud data lakes.
• Extensive knowledge of data warehouse principles, design, and data modeling concepts.
• Experience leading teams of engineers across different geographies.

Preferred Skills

• Experience with AWS Cloud Services.
• Experience using agile engineering practices for rapid data product development.

Key Skills

Education

Any Graduate