Data Engineer

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About Us

AI, Data and Cloud solutions

Generative AI, AI Agents, Data Engineering and Cloud Infrastructure

Microsoft Azure Data Engineering

Role Overview

Data Engineer

Azure Data Factory, ADLS Gen2, Azure Databricks, Microsoft Fabric, Azure Synapse and Azure SQL

Key Responsibilities

• Design and develop scalable

  ETL/ELT data pipelines

  using Azure Data Factory and Microsoft Fabric.
• Build and manage data lakes using

  Azure Data Lake Storage Gen2 (ADLS Gen2)

  .
• Develop distributed data processing solutions using

  PySpark and Azure Databricks

  .
• Work with

  Microsoft Fabric, OneLake and Lakehouse architectures

  .
• Build batch and real-time data pipelines using

  Azure Event Hubs and Spark Streaming

  .
• Integrate data from databases, APIs, files and enterprise applications.
• Develop data transformations and data-quality processes using

  Python, PySpark and SQL

  .
• Work with

  Azure SQL, SQL Server and PostgreSQL

  .
• Implement pipeline monitoring, logging, error handling and performance optimization.
• Support

  AI/ML and Generative AI workloads

  through AI-ready data pipelines and datasets.
• Implement CI/CD for data engineering workloads using

  Azure DevOps and Git

  .
• Follow best practices for data security, governance and access management.
• Collaborate with architects, AI/ML engineers, software engineers and business teams.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Engineering or related field.

• 2–4 years of experience

  in Data Engineering.
• Strong hands-on experience with

  Python and SQL

  .
• Experience building data pipelines on

  Microsoft Azure

  .
• Good understanding of ETL/ELT, data modelling and data warehousing.
• Experience with distributed data processing using

  PySpark/Spark

  .
• Strong analytical and problem-solving skills.
• Good communication and collaboration skills.

Key Skills

• Azure:

  Data Factory, ADLS Gen2, Databricks, Synapse

• Microsoft Fabric:

  OneLake, Lakehouse, Data Pipelines

• Programming:

  Python, SQL, PySpark

• Streaming:

  Azure Event Hubs, Spark Streaming

• Databases:

  Azure SQL, SQL Server, PostgreSQL

• BI:

  Power BI

• DevOps:

  Azure DevOps, Git, CI/CD

• AI/ML:

  Azure ML, MLflow, GenAI Data Pipelines

Good to Have

• Experience with

  Microsoft Fabric

  .
• Experience delivering enterprise Azure data solutions.
• Knowledge of

  Azure AI / Machine Learning

  .
• Experience with Generative AI, RAG or vector-data pipelines.
• Microsoft certifications such as

  DP-203 or DP-700

  .

What We Offer

• Opportunity to work on

  Microsoft Azure + AI

  projects for enterprise customers.
• Exposure to

  Microsoft Fabric, Azure Databricks and Generative AI

  .
• Opportunity to work on modern

  Cloud + Data + AI architectures

  .
• High-ownership role in a fast-growing AI startup.
• Opportunity to work with a global engineering team.