ETL Pipeline Engineer

Role Overview : The Data Engineer is responsible for designing, building, and optimizing data systems that power analytics, reporting, and machine learning across the organization. The role involves developing scalable data models and ETL pipelines, ensuring data integrity, and enabling smarter analytics through BI tools like Looker.

Key Responsibilities

• Data Modelling : Understand the data needs of the business and the key metrics used for analytics and reporting. Design and implement new ways to model the data to calculate these metrics in a more efficient and flexible way.
• ETL Pipeline Development : Develop and maintain ETL pipelines to update the tables which record these metrics for use in business intelligence and machine learning applications. Ensure this data is accurately and efficiently processed and stored. Work with the team to ensure data integrity and accessibility across various platforms.
• Enable Smarter analytics : Work with the risk team to enable easier development and maintenance of key reports and dashboards by using tools such as Looker to provide flexible views from which data can be explored.
• Cross-Functional Collaboration : Work closely with data scientists, data engineers, product managers, and other stakeholders to align data initiatives with business objectives. Facilitate the seamless integration of new data assets and models into operational processes
• Exposure to Python for scripting, data manipulation, and automation.
• Proficiency in SQL is a must have

Skills & Qualifications

1. Strong proficiency in SQL (query optimization, performance tuning, complex joins, stored procedures).

2. Good experience in ETL development

3. Good understanding of data engineering concepts (data modelling, data warehousing, building ETL pipelines).

4. Exposure to Python for scripting, data manipulation, and automation.

5. Strong problem-solving, debugging, and analytical skills.

6. Excellent communication and collaboration abilities.