Sr. Data Engineer

Responsibilities : Create and maintain large-scale data processing systems and infrastructure.

Build robust, performant, and scalable data pipelines to ingest, transform, and store complex data from multiple sources.

Collaborate with data science and software engineering team members to provide required data in an accessible, timely, and accurate manner.

Optimize and refine processes, algorithms, and systems to enhance data quality and reliability.

Ensure data privacy and security compliance.

Implement monitoring, logging, and alert systems to ensure data pipeline health and performance.

Collaborate with infrastructure and IT teams to ensure optimal data storage and retrieval mechanisms.

Drive the optimization, testing, and tooling to improve data quality.

Mentor junior data engineers, imparting knowledge and promoting best practices.

Stay updated with emerging technologies and introduce them as needed to improve the data engineering ecosystem.

Requirements :

Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree is a plus.

5+ years of experience in data engineering, ETL processes, and database systems.

Proficient in SQL, Python, PySpark, and experience with big data platforms.

Experience creating data pipelines and working with workflow management tools.

Strong experience with relational and NoSQL databases.

Working experience in cloud platforms like AWS and Azure.

Excellent communication and collaboration skills.

Experience with Databricks platform, Azure Data Factory, Kedro framework.

Experience with Machine Learning processes.

Relevant Industry Certification.

Role Description :

The Senior Data Engineer will play a pivotal role in building, optimizing, and maintaining our data pipeline architecture, ensuring data quality and accessibility for cross-functional teams. This role will be a key member of our Advanced Analytics team and will focus on building and supporting our data pipelines in a Databricks environment.