1.JD Product Engineering Manager Data Products & Data Platforms
About the Role
We are looking for a Product Engineering Manager with a strong background in Data Product Engineering
to lead the design, development, deployment, and evolution of enterprise-scale data products and
platforms. The ideal candidate combines hands-on data engineering expertise with product lifecycle
ownership and engineering leadership, along with experience in full-stack development, including React.
Key Responsibilities
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Own the end-to-end lifecycle of data products, from product requirements and architecture
to development, deployment, production support, and continuous enhancement.
Lead the engineering of scalable data products, data platforms, pipelines, APIs, and
reusable data services.
Translate business and product requirements into technical architectures, engineering
roadmaps, and scalable solutions.
Drive full-stack development for data products, including React-based user interfaces and
backend services/API integrations.
Establish engineering standards for architecture, code quality, CI/CD, automated testing,
deployment, data quality, monitoring, and observability.
Ensure data products meet requirements for scalability, reliability, performance,
maintainability, and enterprise integration.
Manage engineering delivery, including planning, prioritization, resource allocation,
timelines, risks, and quality.
Lead, mentor, and develop a team of 10+ engineers across data engineering, frontend,
backend, and platform engineering.
Collaborate with Product Management, architects, data engineers, data scientists, and
customers to dene product capabilities and deliver measurable business outcomes.




Drive continuous improvement in engineering practices, team capabilities, and product
delivery.
Qualications
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12+ years of experience in Data Product Engineering, Data Platform Engineering, or related
data-intensive product development.
Demonstrated experience building and owning enterprise-scale data products throughout
their lifecycle.
Strong foundation in data engineering, including data pipelines, integration, distributed
processing, data modelling, and modern data architectures.
Experience leading and mentoring engineering teams of 10+ members.
Hands-on experience with React and integrating frontend applications with backend APIs
and data services.
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Solid understanding of distributed systems, databases, cloud platforms, and software
engineering principles.
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Experience with AWS, Azure, or GCP.
Practical knowledge of CI/CD, automated testing, deployment automation, production
support, and observability.
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Proven ability to make technical architecture decisions while balancing product priorities,
technical debt, quality, and delivery.
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Preferred Qualications
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Experience developing enterprise data products, shared data platforms, reusable data
services, or self-service data capabilities.
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Experience with Apache Spark, Databricks, Snowake, or similar data technologies.
Familiarity with React component architecture, API-driven applications, and
frontend/backend integration.
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Experience with data orchestration, pipeline monitoring, data quality, and data observability.
Exposure to cloud-native architectures, infrastructure automation, and Agile product
delivery.
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Experience with Hadoop ecosystem technologies such as HDFS, MapReduce, Oozie, Hive,
Impala, Spark, Kerberos, or Kafka.
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📌 Product Engineering Manager (Bengaluru)
🏢 Sigmoid
📍 Bengaluru