Associate Data Engineer

Overview

As an Associate Data Engineer, you will support the business analytics agenda by building data models, pipelines and cloud-based data solutions that uncover signals, patterns and trends. You will collaborate with data teams, product owners, engineering leads, data product managers, data modelers, data analysts and other stakeholders.

What you'll do

• Execute the business analytics agenda in conjunction with analytics team leaders.
• Work with external partners who leverage analytics tools and processes.
• Use models and algorithms to uncover signals, patterns and trends that drive long-term business performance.
• Execute the business analytics agenda using a methodical approach that conveys what business analytics will deliver to stakeholders.
• Use data analysis to make recommendations to analytics leaders.
• Design and build scalable, secure and cost-effective cloud-based data solutions.
• Develop and maintain data pipelines to extract, transform and load data into data warehouses or data lakes.
• Implement data quality and validation processes to ensure data accuracy and integrity.
• Ensure efficient data processing and data storage for optimal retrieval performance.
• Coordinate closely within the assigned delivery team to ensure timely completion of deliverables while fulfilling data engineering guidelines and standards.
• Collaborate with data teams, product owners and other stakeholders.
• Stay updated with the latest cloud technologies, data engineering practices, emerging technologies and trends.
• Identify and solve complex data-related challenges.
• Analyze data and draw meaningful insights.
• Apply meticulous attention to data preparation and pipeline development.

What you'll need

• 2 to 4 years of experience in data engineering with good expertise in the required tech stack.
• Experience using data analysis to make recommendations to analytics leaders.
• Understanding of best-in-class analytics practices.
• Knowledge of indicators (KPIs) and scorecards.
• Programming experience with Python, PySpark and SQL.
• Experience with ETL and integration using Databricks, including LDP, Lakeflow Connect and Notebooks.
• Experience with AecorSoft/DataSphere.
• Knowledge of data warehousing, including SCD Types, facts and dimensions, star schema and ETL.
• Understanding of dimensional modelling.
• Knowledge of the Databricks Medallion Architecture, including Bronze, Silver and Gold.
• Experience with AWS cloud services, including S3, Lambda, EC2, Glue and Redshift.
• Experience with scheduling technologies, including Lakeflow Jobs and Airflow.
• Effective communication skills to collaborate with Engineering Leads, Data Product Managers, Data Modelers, Data Analysts and stakeholders.
• Ability to stay updated with emerging technologies and trends in the data engineering field.

Nice to have

• Knowledge of BI tools such as Tableau, Excel, Alteryx, R and Python.
• Experience with the Erwin tool.
• Exposure to GenAI tools such as Genie, Kiro and Gemini.
• Experience with PowerBI.
• Experience with GenBI.

Details

• Location: Mumbai, India.
• No relocation support is available.
• Employment type: Regular.