Lead Azure ETL Developer (757760)

Client is looking for an experienced and highly skilled Azure Lead Data Engineer to lead the design, development, and optimization of cloud-based data solutions. The ideal candidate will have strong technical expertise in Azure cloud services, data engineering, and analytics, with a proven ability and responsible for implementing robust ETL/ELT pipelines, optimizing data processing workflows, and collaborating with cross-functional teams to deliver high-quality data solutions. Candidates should have architect-level experience in designing complex data architectures.

Required Skills & Qualifications:

Proven experience in data engineering, with at least 5 years of hands-on experience in Azure technologies (Azure Data Factory, Databricks, Azure Synapse, Data Lake, etc.).

Strong expertise in building and optimizing scalable data pipelines for cloud-based platforms.

Advanced proficiency in PySpark, Spark, SQL, and other data engineering tools.

Experience with Azure services including Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL.

Expertise in data modeling, data integration, and ETL/ELT processes.

Hands-on experience inSQL Server (SSIS,SSRS, SSAS), ORACLE, T-SQL, Azure SQL Database, Azure SQL Datawarehouse.

Good Experience with Dataverse, Share point online, other Api's for Data extraction.

In-depth understanding of cloud architecture, including cloud storage, data lakes, and data warehouses.

Architect-level experience in designing, building, and optimizing large-scale, complex data solutions on Azure.

Familiarity with data warehousing architectures such as MOLAP, ROLAP, ODS, and EDW.

Hands-on experience with version control systems such as Git and managing deployment pipelines using Databricks Asset Bundles.

Familiarity with Agile methodologies and working in Agile project environments.

Experience with AI technologies like Microsoft Fabric, OpenAI, or similar is a plus.

Strong expertise in Snowflake data solutions, including data modeling, querying, and performance optimization.

Hands-on experience with Azure DevOps for continuous integration and delivery.

Experience in developing real-time data processing solutions and streaming frameworks (e.g., Spark Streaming).

Strong communication skills to effectively interact with technical and non-technical stakeholders.

Preferred Skills & Experience:

Knowledge of machine learning models and AI applications in data engineering.