Lead Data Infrastructure Specialist

4 days ago


Belgaum, Karnataka, India beBeeLeadership Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Job Overview

This is an exciting opportunity to take on a leadership role in our data engineering team. As a Lead Data Platform Engineer, you will be responsible for designing and implementing production-grade data pipelines, as well as leading delivery of complex projects.

Key Responsibilities:

  • Technical Leadership: Provide technical guidance and direction to the team, ensuring that projects are delivered on time and within budget.
  • Data Pipeline Design: Design and implement reliable batch and change-driven pipelines, including schema evolution and failure handling.
  • Architecture Direction: Define target states and data contracts, make build/buy calls, and author RFCs to drive cost/performance guardrails and reliability patterns.
  • Collaboration and Communication: Work closely with cross-functional teams to ensure effective communication and collaboration, and provide clear written and verbal comms.

Requirements

To succeed in this role, you will need:

  • Proven leadership experience, with a track record of leading engineers or owning large, multi-team projects.
  • Strong SQL skills, including tuning, indexing, and query plans, as well as solid RDBMS fundamentals.
  • Experience with Python for data work and services, as well as shell scripting.
  • Terraform and IaC fundamentals, as well as CI/CD experience.
  • Cloud experience, preferably with Azure, but also AWS.
  • Knowledge of data integration, workflow orchestration, APIs, and observability.
  • A testing mindset, with a habit of writing tests for code and SQL.
  • Effective communication and collaboration skills.

Preferred Qualifications

While not required, we would love to see experience with:

  • Mentoring, interviewing, onboarding, and raising code quality standards.
  • Regulatory compliance awareness and how it impacts design and operations.
  • Analytics exposure, including dim/fact modeling and BI consumption patterns.
  • Data platform architecture exposure, including storage/layout choices and governance concepts.
  • Familiarity with Kafka, streaming/message queues, and columnar formats.
  • Experience with cloud monitoring stacks.


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