Head of Data Engineering
New
Based in IndiaFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- 3+ years of experience managing and developing engineering teams; 5+ years of hands-on experience with programming languages
- Required Skills
- PythonETLGCPJavaNosqlCI/CDScala
Requirements
- Proven experience leading data engineering functions within a high-growth, scale-up, or technology-driven environment.
- 3+ years of experience managing and developing engineering teams, with a strong ability to mentor and inspire technical talent.
- 5+ years of hands-on experience with programming languages such as Python, Java, or Scala for building complex data systems.
- Deep knowledge of data architecture, data warehousing, big data technologies, and cloud infrastructure.
- Strong experience working with relational and NoSQL databases at scale.
- Expertise with the Google Cloud Platform (GCP) ecosystem and modern cloud-based data solutions.
- Demonstrated ability to design secure, reliable, and high-performance data pipelines.
- Strong technical leadership skills with the ability to drive engineering excellence and ownership.
- Excellent communication and collaboration skills, with the ability to work effectively across multiple teams.
- Advanced degree in Computer Science, Engineering, or a related field is a plus.
Responsibilities
- Design, develop, and continuously improve a scalable data architecture capable of supporting rapid global expansion.
- Define engineering standards for data pipelines, including CI/CD practices, automation, version control, and operational excellence.
- Ensure data reliability, security, governance, and performance across platforms supporting analytics and machine learning initiatives.
- Lead strategic technology decisions, including the selection and adoption of cloud platforms, tools, and data engineering solutions.
- Build and mentor high-performing data engineering teams, fostering technical ownership, collaboration, and continuous improvement.
- Guide the development of efficient ETL/ELT solutions and modern data workflows.
- Partner with business, product, analytics, and technical stakeholders to translate complex requirements into scalable solutions.
- Establish processes that improve data quality, accessibility, and the overall effectiveness of the data organization.
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