Job Description

We are seeking an experienced Data Engineer to design, develop, and maintain scalable data storage, integration, and processing solutions on the Azure platform. The ideal candidate will have strong technical expertise in Azure services, SQL, Python, and Databricks, along with a solid understanding of ETL processes and data governance principles.

Job Responsibilities:

Design and implement data storage solutions using Azure SQL Database, Azure Data Lake, and Azure Blob Storage. Develop and maintain data pipelines for ingestion, processing, and transformation using Azure Data Factory or similar tools. Build and optimize data models to support analytics and reporting needs. Work with Azure Databricks and Apache Spark to assemble and process large, complex data sets. Implement data validation, cleansing, and quality assurance procedures. Optimize database performance for efficient query execution. Ensure data security, privacy, and compliance with organizational standards. Collaborate with data engineers, analysts, and other stakeholders to deliver reliable and scalable data architectures. Participate actively in Agile/Scrum ceremonies and contribute to sprint deliverables.

Job Requirements:

10+ years of total IT experience, with at least 5+ years in data engineering. Strong hands-on experience with the Azure stack (Data Factory, Databricks, Data Lake, SQL Database, Blob Storage). Proficiency in SQL and Python. Experience with ETL processes and data integration frameworks. Knowledge of data modeling, data warehousing, and big data technologies. Familiarity with Azure DevOps and data governance best practices. Excellent problem-solving, communication, and collaboration skills.

Desired Skills:

Experience in optimizing ETL and data transformation workflows. * Exposure to advanced analytics or machine learning integration on Azure platforms.