Senior Data Engineer | GPM

We are hiring on behalf of our client, a leading ad-tech company, supported by a Nasdaq-listed parent company with over 5,000 employees worldwide.

Role Overview:

We are looking for a talented  Senior Data Engineer with expertise in Relational databases and NoSQL databases, ETL process, Kafka, and data warehouses like Snowflake, Redshift, cloud platforms like AWS, GCP, or Azure to join a highly collaborative and agile team. If you have experience in product companies or startups and thrive on solving complex technical challenges, this is the perfect opportunity for you!

Experience: 5-9 years
Location: Chennai
work mode: Hybrid - flexible

Qualifications: 

• 5-9 years of experience in data engineering, with a focus on building and managing data pipelines.
• Strong proficiency in relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).
• Experience in building data pipelines with data warehouses like Snowflake, Redshift 
• Experience in processing unstructured data stored from S3 using Athena, Glue etc.
• Hands-on experience with Kafka for real-time data streaming and messaging.
• Solid understanding of ETL processes, data integration, and data pipeline optimization.
• Proficiency in programming languages like Python, Java, or Scala for data processing.
• Experience with Apache Spark for big data processing and analytics is an advantage
• Familiarity with cloud platforms like AWS, GCP, or Azure for data infrastructure is a plus.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills, with the ability to work effectively in a team environment.

Key Responsibilities:

• Design, build, and maintain efficient and scalable data pipelines to support data integration and transformation across various sources.
• Work with relational databases (e.g., MySQL, PostgreSQL, etc.) and NoSQL databases (e.g., MongoDB, Cassandra, etc.) to manage and optimize large datasets.
• Utilize Apache Spark for distributed data processing and real-time analytics.
• Implement and manage Kafka for data streaming and real-time data integration between systems.
• Collaborate with cross-functional teams to gather and translate business requirements into technical solutions.
• Monitor and optimize the performance of data pipelines and architectures, ensuring high availability and reliability.
• Ensure data quality, consistency, and integrity across all systems.
• Stay up-to-date with the latest trends and best practices in data engineering and big data technologies.