What you'll do:

• Hands-on expertise in one or more Amazon Web Services (AWS) technologies, such as
• Kinesis, S3, Redshift, Athena, Lambda
• Experience with following aspect of data engineering:
• Building and optimizing - big data- data pipelines, architectures and data sets.
• Manipulating, processing and extracting value from large, disconnected datasets
• Development of data pipeline and workflow management tools: Azkaban, Luigi,Airflow, etc.-
• Good experience with at least one ETL tool like Talend, Informatica etc.
• Build processes supporting data transformation, data structures, metadata,dependency and workload management.
• Expertise in at least one of the NoSQL databases.
• This person should be open to work in afternoon shifts (starting around 12 noon or 1 as we may need some overlap time with our US/Europe clients)

What makes you a great fit :

• Hands-On experience in AWS technologies (AWS S3, AWS EMR, Athena etc.), Redshift, Python
• Must have around 5+ years of experience in delivering data engineering projects
• Have strong knowledge in ETL, Data warehousing, Business intelligence
• Should be able to configure pipelines to ingest data from landing zone to the data platform.
• Should be able to configure pipelines to ingest and process data from supplier landing zone to the data platform.
• Monitor and respond to scheduled workloads that feed data from and to the data platform.
• Communicate and work on schema drift and/or other Supplier issues.
• Create and execute quality scripts to monitor and maintain the accuracy of our data.
• HandsOn experience with Databricks or snowflake is a huge plus.