Lead Data Engineer

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LTIMindtree

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Python kafka Airflow BigQuery pySpark CI Google Cloud Analytics play Strategy

Job Description

Skill: Lead Data Engineer

Experience: 10 to 12/13 years

Location: Hyderabad/Chennai

Job Description:

We are looking for a seasoned Data Engineer with strong expertise in GCP, Kafka, and PySpark, along with proven experience in leading teams or driving technical initiatives. The ideal candidate will play a key role in designing scalable data platforms, mentoring team members, and delivering high-quality data solutions.

Key Responsibilities:

  • Lead the design, development, and deployment of scalable data pipelines and data platforms.
  • Architect and implement real-time and batch data processing solutions using Kafka and PySpark.
  • Work extensively with Google Cloud Platform (GCP) services for data engineering and analytics.
  • Provide technical leadership, guidance, and mentorship to junior and mid-level engineers.
  • Collaborate with cross-functional teams including Data Scientists, Analysts, and business stakeholders.
  • Ensure high data quality, performance optimization, and system reliability.
  • Drive best practices in coding, data architecture, and data governance.
  • Participate in solution design discussions and contribute to long-term data strategy.
  • Troubleshoot complex data issues and provide scalable solutions.

Mandatory Skills:

  • Strong hands-on experience with Kafka (real-time data streaming)
  • Expertise in Python (PySpark) for large-scale data processing
  • Hands-on experience with Google Cloud Platform (GCP)
  • Strong understanding of Big Data ecosystem and distributed systems

Leadership / Additional Skills:

  • Experience in leading teams or handling end-to-end project delivery
  • Strong problem-solving and decision-making skills
  • Ability to interact with stakeholders and drive technical discussions

Good to Have:

  • Experience with data orchestration tools (e.g., Airflow)
  • Knowledge of BigQuery or other data warehousing tools
  • Exposure to CI/CD and DevOps practices
  • Experience with data modeling and architecture


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