Senior Data Engineer

Help design and deliver a modern data platform for a US-based client’s engineering team as a Senior Data Engineer.

About the Client
Our client is a global customer experience technology and consulting company and a long-standing, top-tier Microsoft partner. Its Microsoft practice works across Dynamics 365, Power Platform, Azure, and Microsoft 365.

The client’s teams bring together CX engineers, developers, data scientists, and solution architects who design, deliver, and support complex, fully integrated digital solutions for enterprise clients.

Your impact
You’ll work across Microsoft Azure, Microsoft Fabric, and Azure Databricks to build scalable, secure, and governed lakehouse platforms that support analytics, Generative AI, and Agentic AI.

Working alongside architects, data scientists, and client stakeholders, you’ll ingest, clean, prepare, and deliver trusted data, and build the APIs that connect it to downstream applications and reporting.

What makes you a great fit
5+ years in technology, with significant experience in enterprise data platforms, cloud, and analytics
Strong experience building Data & Analytics solutions on Microsoft Azure
Exposure to the Microsoft Azure data ecosystem (Azure Data Factory, Microsoft Fabric, ADLS Gen2) and/or Azure Databricks
Strong technical foundation in SQL, Python, Spark, distributed processing, data modeling, integration patterns, and APIs
Strong understanding of Medallion Architecture, data products, semantic layers, batch and streaming architectures, and event-driven integration
Knowledge of Azure security: Entra ID, RBAC, managed identities, Key Vault, VNets, Private Link/private endpoints
Understanding of ETL/ELT concepts and the end-to-end data lifecycle, from ingestion through activation
Familiarity with building or consuming APIs for data integration
Familiarity with version control (Git) and basic CI/CD concepts
Upper-Intermediate English level or higher
Nice to have
Experience with Delta Lake and Unity Catalog
Experience with Azure DevOps
What you will do
Design, build, and maintain batch and streaming data pipelines using Microsoft Fabric, Azure Data Factory, and Azure Databricks, with Python, PySpark, and SQL
Ingest data from structured, semi-structured, and unstructured sources (databases, APIs, files, and event streams) into governed lakehouse environments
Support the full data journey on client engagements: ingestion, cleaning, preparation, transformation, and delivery of analytics-ready datasets