Data Engineer

Role Overview

As a Data Engineer, you will design and build scalable, secure, and cost-effective cloud-based data solutions. You will develop and maintain data pipelines to extract, transform, and load data into data warehouses or data lakes, ensuring data quality and validation processes to maintain data accuracy and integrity.

What You Will Do

You will execute the business analytics agenda in conjunction with analytics team leaders, use models/algorithms to uncover signals/patterns and trends to drive long-term business performance, and collaborate closely with data teams, product owners, and other stakeholders to stay updated with the latest cloud technologies and best practices.

Why It Might Be a Fit

You will have the opportunity to drive your future and accelerate your career, and you will have the ability to identify and solve complex data-related challenges, effective communication skills to collaborate with Engineering Leads, Data Product Managers, Data Modeler, Data Analysts, and stakeholders, and the capacity to analyze data and draw meaningful insights.

Requirements

• Programming: Python, PySpark, SQL
• ETL & Integration: Databricks (LDP, Lakeflow Connect, Notebooks), AecorSoft/DataSphere
• Data Warehousing: SCD Types, Fact & Dimensions, Star Schema, ETL
• Data Modeling: Dimensional modelling understanding, Erwin tool (Optional)
• Medallion Architecture: Bronze, Silver, Gold (Databricks Medallion Architecture)
• AWS Cloud Services: S3, Lambda, EC2, Glue, Redshift
• GenAI exposure: Genie/Kiro/Gemini etc.
• Scheduling Technologies: Lakeflow Jobs, Airflow
• Visualization (Optional): PowerBI (Optional), GenBI (Optional)

Benefits

• Notice Period: 0-3 Months allowed