As a Data Infrastructure Engineer, you will be at the design, build, maintain and improve our data infrastructure on Cloud, which enables us to make Income data driven organisation. In this role, you would also get the opportunity to work with world-class big data and cloud
services, such as: AWS/GCP, Glue, Spark, DBT, Airflow, Tableau and PowerBI.
Responsibilities:
Work with data engineering and machine learning teams to improve our data infrastructure for increased reliability, maintainability, and scalability.
- Architect and design solutions to improve our data delivery capabilities, data quality monitoring, and data pipeline lifecycle.
- Architect and administer our cloud applications such as AWS Glue, Sagemaker, LakeFormation, iceberg lakehouse, etc.
- Managing Regression Testing Suite , Continuous Integration and Contnuous deployment Pipelines.
Qualifications:
• 1 to 3 years of designing and building production data pipelines from ingestion to consumption in a cloud environment using SQL and Python.
• Experience in cloud application architecture & administration in AWS or Azure. Hands-on experience designing, building and operationalizing largescale enterprise data solutions and applications. (Airflow, Databricks, Snowflake, Serverless Functions, Cloud storage preferred).
• Background in custom ETL design, implementation, and maintenance. Hands-on experience with Unix/Linux Command Line Interface (CLI).
