Senior Data Engineer

Roles & Responsibilities:

• Design, develop, and maintain robust data pipelines using Databricks, Azure Analysis Services (AAS), and Azure Data Factory.
• Perform data modeling and transformation to ensure data quality and consistency across systems.
• Implement and optimize ETL processes for efficient data flow.
• Ensure data accessibility and compatibility with various business intelligence and reporting tools, facilitating seamless integration between cloud-based data services and end-user analytics platforms.
• Manage and optimize cloud solution operations, focusing on performance, scalability, and cost-effectiveness.
• Collaborate with cross-functional teams to understand data needs and provide solutions.
• Implement data governance and security best practices.
• Continuously improve data pipeline architecture and processes.

Skills & Experience

• 3-5 years of experience in data engineering or a similar role.
• Strong proficiency in Databricks, Azure Analysis Services, and Azure Data Factory.
• Expertise in data modeling, ETL processes, and data transformation techniques.
• Solid understanding of cloud computing concepts and experience with Azure cloud services.
• Proficiency in SQL and experience with NoSQL databases.
• Knowledge of data visualization tools and reporting requirements.
• Experience with version control systems (e.g., Git) and CI/CD pipelines.
• Excellent problem-solving skills and attention to detail.
• Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.
• Experience with Python, Scala, or other programming languages commonly used in data engineering.
• Familiarity with big data technologies such as Hadoop, Spark, or Hive.
• Knowledge of data governance and compliance requirements.
• Certifications in relevant Azure technologies or data engineering.