Microsoft Data Engineer

At KPMG, within the Cloud & Data Engineering service line, we are seeking a talented Azure Data Engineer (Consultant) to support the design and delivery of modern data platforms and data engineering solutions for our clients. You will work with senior engineers and architects to build scalable data pipelines, integrate diverse data sources, and deliver high-quality, cloud-native data solutions. The team enables clients to accelerate their digital transformation journey using Azure's powerful data and analytics capabilities.

Roles & responsibilities

• Contribute to the development of data ingestion, transformation, and integration pipelines on Azure

• Support the implementation of ETL/ELT workflows using Azure Data Factory, Synapse, Databricks, and other Azure-native services

• Participate in building and maintaining data lakes, data warehouses, and analytical datasets

• Work with senior team members to understand client requirements and translate them into technical tasks

• Perform data cleaning, processing, validation, and quality checks

• Develop SQL/PySpark code for ingestion, transformation, and analytical data preparation

• Assist in optimizing pipeline performance, storage efficiency, and compute consumption on Azure

• Contribute to documentation, technical design reviews, sprint activities, and engineering best practices

• Troubleshoot pipeline failures, data issues, and operational incidents

• Stay updated with Azure data engineering tools, cloud trends, and modern data architecture practices

Educational qualifications

• A bachelor's or master's degree in Engineering, Computer Science, or equivalent

• Relevant Azure Certifications (Azure Data Fundamentals(DP-900), Azure Fundamentals(AZ-900), Fabric Data Engineer Certificate (DP-700, preferred but not mandatory)

Work experience

• 3-6 years of experience in data engineering, data integration, or cloud analytics

• Hands-on exposure to Azure data platform services and enterprise data engineering concepts

Mandatory technical & functional skills

• Working experience with Azure Data Factory, Azure Data Lake Storage, Azure Databricks and Azure Synapse Analytics

• Good understanding of ETL/ELT concepts, data ingestion, and data transformation frameworks

• Proficiency in SQL and basic experience with PySpark or Python

• Experience working with structured and semi-structured data formats (Parquet, JSON, CSV, Avro)

• Understanding of data modeling concepts (dimensional modeling basics)

• Familiarity with CI/CD, Git repositories, and basic DevOps workflows

• Understanding of Azure security basics — RBAC, access control, networking fundamentals

• Experience working in an Agile environment, contributing to sprints, and collaborating with cross-functional teams

• Ability to communicate clearly and collaborate effectively with peers and senior team members

Preferred technical & functional skills

• Exposure to Azure Databricks, Fabric or Spark-based data engineering

• Experience with Azure Functions or Logic Apps for data processing

• Familiarity with data lineage or Microsoft Purview

• Knowledge of building data quality rules or validation scripts

• Understanding of Power BI datasets, dataflows, or semantic models

• Basic understanding of Generative AI concepts, LLM data preparation, or Azure OpenAI integrations