Lead Data Engineer

4 days ago

Bengaluru, Karnataka, India FYERS Full time ₹ 20,00,000 - ₹ 25,00,000 per year

We are a fast-scaling, data-first organization building intelligent data infrastructure to empower real-time, data-driven decisions across the business. We're seeking a Senior Data Engineer / Team Lead to architect scalable data platforms and lead a team of high-performing data engineers. This is a hands-on technical leadership role where you will not only guide the team of 2-4 Engineers but also actively contribute to designing and implementing data solutions.

Key Responsibilities:

Technical Leadership:

  • Architect and design scalable, efficient, and reliable data pipelines and platforms and Lead the adoption and best practices for Date Engineering tools.
  • Ensure high standards for data quality, reliability, governance, and security.
  • Drive the team's technical roadmap, identifying areas for innovation and optimization

People & Project Leadership:

  • Lead and mentor a team of data engineers, fostering growth, ownership, and excellence.
  • Manage sprint planning, code reviews, and technical delivery in an agile environment.
  • Collaborate with Product, Analytics, and Data Science teams to align on data needs and priorities.
  • Own end-to-end delivery of projects, ensuring scalability, performance, and sustainability.

Requirements

  • 8–10 years of experience in data engineering or backend engineering with significant data pipeline responsibilities.
  • Expertise in Python for data engineering tasks, including data transformation and orchestration.
  • Hands-on experience with Kafka for real-time streaming and event-driven architectures.
  • Proven experience with Airflow or equivalent scheduling/orchestration tools.
  • Deep knowledge of Databricks and Apache Spark for distributed data processing.
  • Proficient in SQL, with strong understanding of relational and distributed databases (e.g., Snowflake, Redshift, BigQuery).
  • Experience in designing data architectures on cloud platforms (AWS, Azure, or GCP).
  • Solid understanding of data modeling, data warehousing, and data governance.
  • Experience in managing cost optimization and performance in cloud-based data platforms.
  • Familiarity with MLOps or data products serving ML pipelines.

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