Data Engineering Lead

1 day ago

Ahmedabad, Gujarat, India beBeeDataEngineering Full time ₹ 12,00,000 - ₹ 15,00,000

Job Description

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  • Are you a skilled data engineer looking to lead a team and drive the design, development, and deployment of scalable data pipelines? We are seeking a Data Engineering Manager to oversee the development of frameworks for data ingestion, integration, and governance.">
  • This is a critical leadership role for someone eager to solve complex data problems, influence architecture, and collaborate cross-functionally in a fast-paced environment.">
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Key Responsibilities:

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  • Lead and mentor a team of data engineers delivering high-quality, production-grade data solutions.">
  • Oversee development of frameworks for data ingestion, integration, and governance.">
  • Ensure data platform stability, scalability, and adherence to operational SLAs.">
  • Collaborate with product owners and stakeholders to shape and execute data strategy.">
  • Build and maintain APIs, DevOps pipelines, and support CI/CD for data products.">
  • Act as functional data SME, owning the lifecycle of critical data assets.">
  • Champion Agile and modern engineering practices in delivery cycles.">
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Required Skills & Experience:

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  • Bachelor's or Masters in Computer Science, IT, Statistics, or related field.">
  • 3+ years of hands-on experience in data engineering and software development.">
  • Proficiency in Python coding experience, SQL, and data testing frameworks.">
  • Experience with cloud platforms and building APIs.">
  • Strong grasp of DevOps, CI/CD, and Agile delivery methodologies.">
  • Track record in designing and maintaining enterprise-grade data pipelines.">
  • Ability to collaborate across teams and drive change in a dynamic environment.">
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What You Bring:

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  • A mindset of ownership, innovation, and continuous improvement.">
  • Passion for mentoring and team development.">
  • Strong communication and stakeholder management skills.">
  • Eagerness to challenge the status quo and drive impactful outcomes.">
  • Collaborative, transparent approach to building scalable data ecosystems.">
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