Description

Key Skills: Data Engineering, Snowflake, Spark, Kafka, Airflow, ETL/ELT, Data Warehouses, Data Lakes, Team Leadership, Big Data

Good to Have Skills: Experience in cloud-based data ecosystems, building AI/ML data pipelines, working with AI/ML data platforms or MLOps environments, experience in fast-paced product organizations, Flink, Databricks, dbt technologies.

Roles & Responsibilities:

• Lead and manage a team of Data Engineers to drive technical excellence and delivery.
• Drive execution, delivery, and day-to-day technical leadership for the engineering team.
• Own team planning, task prioritization, and execution quality for data engineering projects.
• Mentor engineers and support their professional growth and development within the organization.
• Collaborate closely with Product, Architecture, Analytics, and other engineering teams across the company.
• Lead the design, development, and maintenance of scalable data solutions, tools and features.
• Ensure high standards for reliability, monitoring, observability, and data quality across all systems.
• Participate in architectural and technical decisions within the broader Data platform ecosystem.
• Support production operations, troubleshooting, and continuous improvement efforts for data infrastructure.
• Promote engineering best practices, code quality, testing, and operational excellence standards.
• Contribute hands-on to features, infrastructure and POC evaluations for new technologies.
• Help prepare the organization's data ecosystem for AI and ML initiatives and implementations.

Experience Required: 10+ years of hands-on experience in Data Engineering within large data environments spanning multiple stakeholders and petabytes of data. 3+ years of experience as people leader and team manager. Hands-on experience building and maintaining large-scale data platforms

Key Skills

Education

Any Graduate