Responsibilities:
Design and build scalable data pipelines using AWS services like AWS Glue, Amazon Redshift, and S3.
Develop efficient ETL processes for data extraction, transformation, and loading into data warehouses and lakes.
Create and manage applications using Python, SQL, Databricks, and various AWS technologies.
Quickly develop innovative Proof-of-Concept (POC) solutions and services to address emerging needs.
Provide Run/DevOps support and manage the ongoing operation of data services.
Automate repetitive tasks and build reusable frameworks to improve efficiency.
Collaborate with teams to design and develop data products that support marketing and other business functions.
Ensure our data services are reliable, maintainable, and seamlessly integrated with existing systems.
Required skills and experience:
3-5 years of experience with DevOps automation tools like GitLab, Bitbucket, Jenkins, and Maven.
Hands-on experience with AWS services including S3, Lambda, API Gateway, and SQS.
Strong skills in data engineering on AWS, with proficiency in Python.
Experience with batch job scheduling and managing data dependencies.
Knowledge of data processing tools like Spark, Hive, Kafka, and Airflow.
Experience with automated testing tools such as MUNIT and Selenium.