What you'll do?

1. Building and optimizing - big data- data pipelines, architectures and data sets.

2. Manipulating, processing and extracting value from large, disconnected datasets

3. Development of data pipeline and workflow management tools: Azkaban, Luigi,

Airflow, etc.-

4. Good experience with at least one ETL tool like Talend, Informatica etc.

5. Build processes supporting data transformation, data structures, metadata,

dependency and workload management.

6. Expertise in at least one of the NoSQL databases.

What makes you a great fit?

• 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

• Hands-On experience in AWS technologies (AWS S3, AWS EMR, Athena etc.), Redshift, Python

• Must have around 6-12 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.

his 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)