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Data Engineer

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Onsite

Data Engineer

Brahma

Data Engineer

Skills

Google Cloud PlatformSQL QueriesBig DataData EngineeringDockerPythonMachine LearningAIAWSLinuxKubernetesAzure

8 months ago

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Important information


Location:

Maharashtra, India

Work mode:

Onsite

Published on:

7 September 2026

What they need


As a Data Engineer, you’ll architect and maintain the pipelines that power our products and services. You’ll work at the intersection of ML, media processing, and infrastructure; owning the data tooling and automation layer that enables scalable, high-quality training and inference. If you’re a developer who loves solving tough problems and building efficient systems, we want you on our team.

Key Responsibilities

  • Design and maintain scalable pipelines for ingesting, processing, and validating datasets with main focus visual and voice data.
  • Work with other teams to identify workflow optimisation potential, design and develop automation tools, using AI-driven tools and custom model integrations and scripts.
  • Write and maintain tests for pipeline reliability.
  • Build and maintain observability tooling in collaboration with other engineers to track data pipeline health and system performance.
  • Collaborate with data scientists, operators, and product teams to deliver data solutions.
  • Debug and resolve complex data issues to ensure system performance.
  • Optimise storage, retrieval, and caching strategies for large media assets across environments.
  • Deploy scalable data infrastructure using cloud platforms as well as on-premise and containerization.
  • Deepen your knowledge of machine learning workflows to support AI projects.
  • Stay current with industry trends and integrate modern tools into our stack.

Must Haves

  • 3+ years in data engineering or related backend/infrastructure role.
  • Strong programming skills in Python or similar languages.
  • Experience with software development lifecycle (SDLC) and CI/CD pipelines.
  • Proven experience building and testing data pipelines in production.
  • Proficiency in Linux.
  • Solid SQL knowledge.
  • Experience with Docker or other containerisation technologies.
  • Proactive approach to solving complex technical challenges.
  • Passion for system optimisation and continuous learning.
  • Ability to adapt solutions for multimedia data workflows.

Nice to Have

  • Experience with Kubernetes (k8s).
  • Knowledge of machine learning or AI concepts.
  • Familiarity with ETL tools or big data frameworks.
  • Familiarity with cloud platforms (e.g., AWS, GCP, Azure).

About You

  • Innovative
  • Like challenges
  • Adaptable
  • Calm under pressure
  • Strong communication abilities

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