Team Lead, Data Engineering at Oxygen X

The position

We are seeking an experienced Team Lead Data Engineer to guide our data engineering team in designing and building scalable data infrastructure. This role demands strong technical expertise in AWS services, data pipelines, and modern data engineering tools, with a focus on hands-on implementation. You will lead the team in optimizing data processing, storage, and system performance while ensuring high-quality, efficient solutions.

Responsibilities

• Lead and mentor a team of data engineers, driving best practices in data architecture and engineering.
• Bridges the gap between the team’s technical work and higher-level project goals, often collaborating with other technical leads or architects.
• Design, build, and optimize scalable data pipelines using AWS
• Implement cost-effective and efficient AWS data infrastructure, leveraging best practices for cost management and performance optimization.
• Oversee data storage, processing, and security across databases like Postgres, Oracle, and SQL.
• Collaborate with data analysts, data scientists, and business teams to understand data needs and develop highly available, reliable, and scalable data solutions.
• Ensure data quality, integrity, and governance, implementing robust monitoring and validation mechanisms.
• Coordinates tasks within the team, ensuring projects are delivered on time and meet technical standards.

Requirements

• Bachelor's or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.
• 7+ years of hands-on experience in data engineering, with a track record of delivering scalable data solutions.
• Deep proficiency with AWS data engineering tools, including S3,Redshift,Glue and Lambda
• Extensive experience designing and optimizing scalable ETL/ELT pipelines within AWS, using tools like AWS Glue, Step Functions, or third-party integrations
• Advanced proficiency in Python, SQL and Spark with strong data modeling experience.
• Strong knowledge of cost optimization strategies for AWS-based data pipelines and storage.
• Hands-on experience with Databricks, NoSQL and SQL databases.
• Hands-on knowledge of building and maintaining data lakes and distributed processing.
• Understanding of how to design systems that handle large-scale data growth and maintain performance under load.
• Experience in fintech or digital lending is a plus.