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Data Engineer

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Onsite

Data Engineer

Digital Edge Dc

Data Engineer

Skills

SQL QueriesData EngineeringDockerPythonData VisualizationKafkaDatabricksCybersecurityData AnalysisMachine LearningAIKubernetesMQTTPower BIAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Mumbai, Maharashtra, India

Work mode:

Onsite

Published on:

25 August 2026

What they need


Who we are:

Digital Edge DC (Digital Edge) is a leading data center platform company, established to transform digital infrastructure in Asia. We seek to build the foundation for the world s digital future, helping organizations to grow sustainably and empowering the populations they serve.

Through building and operating state-of-the-art, energy-efficient data centers rich with connectivity options, we bring new colocation and interconnect options to the Asian market, making infrastructure deployment in the region easy, efficient and economical. Backed by Stonepeak, a leading alternative investment firm specializing in infrastructure and real assets, Digital Edge has in excess of US$1.6 billion in committed capital.

Founded in late 2019, the company has grown rapidly across multiple markets in the region, with 30+ data centers in operations and under construction, and this role is an exciting opportunity to join the team as we further expand our footprint across Asia.

Our values:

  • Respect: We embrace diversity and collaboration.
  • Innovation: We share ideas and solve problems.
  • Strive: We are driven and determined.
  • Excellence: We seek to deliver the best.
  • Responsibility: We do what s right for our people and the planet.

What we need:

As a Data Engineer, you will be responsible for building robust data pipelines and ensuring seamless integration across multiple systems to support business insights and analytics.

Key responsibilities:

  • Build Data Pipelines : Develop and optimize scalable end-to-end data pipelines (batch and real-time) for structured and unstructured data from a variety of sources (APIs, databases, logs, etc.).

  • Data Modeling & Warehousing : Design and implement efficient, scalable, and intuitive data models and maintain data lakes for reporting and analytics purposes.

  • Platform Ownership & Optimization : Take ownership of critical parts of our data platform. Proactively monitor pipeline performance, identify bottlenecks, and implement optimizations for cost, reliability, and speed.

  • Data Quality & Governance : Implement and advocate for data quality frameworks, data lineage, and governance best practices to ensure the accuracy and trustworthiness of our data assets.

  • Collaboration : Work closely with stakeholders to translate business needs into technical solutions.

  • Tooling & Innovation : Evaluate and recommend new technologies and tools to continuously improve our data ecosystem. Stay current with emerging trends in data engineering.

  • Actively champion and implement the organization s policies on health & safety, environment, energy, quality, information security, and business continuity, ensuring adherence to incident reporting, legal, and regulatory requirements.

The successful candidate:

Required:

  • Bachelor s or master s degree in computer science, Engineering, or a related field, or equivalent practical experience.
  • 5+ years of professional experience in data engineering or analytics role.
  • Advanced proficiency in SQL and Python , with experience in building and optimizing data pipelines
  • Hands-on experience with Databricks and Apache Spark , integrating with Azure Services . (e.g. Data Lake Storage, SQL Database, Event Hubs)
  • Proficiency in data visualization and BI tools, preferably Power BI , with experience in developing complex reports and data models
  • Strong understanding of data warehousing concepts, data and ETL/ELT best practices.
  • Familiarity with data lakehouse architectures (e.g., Delta Lake, Iceberg, Hudi) is a plus.
  • Strong problem-solving and communication skills.

Preferred (Nice-to-Haves):

  • Experience with real-time data streaming (e.g., Kafka ).
  • Understanding of IoT protocols (e.g. MQTT, OPC-UA, Modbus ) is an advantage.
  • Knowledge of containerization technologies like Docker and Kubernetes .
  • Understanding of AI/ML concepts is a plus.

Join us to shape the future of Digital Infrastructure in Asia.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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