Data Analytics, Supervisor

You will collaborate with cross-functional teams, including data scientists, analysts, engineers, and business stakeholders, to understand requirements and translate them into scalable technical solutions. You will facilitate business requirements sessions and conduct data analysis to accurately identify and specify the data needed to support impactful business objectives. Additionally, you will lead the design and implementation of data engineering solutions using the Microsoft Data Stack (Azure Synapse, Azure Data Lake, Data Factory, Databricks, Power BI) and Snowflake. Your responsibilities will include overseeing solution delivery engagements, architecting and developing scalable data pipelines, implementing data governance, and leading the design and development of Semantic Models and Reports/Dashboards based on business requirements. You will also optimize data storage and retrieval performance, monitor health and performance metrics, troubleshoot issues, and lead and mentor a team of data engineers and analysts. **Key Responsibilities:** - Collaborate with cross-functional teams to translate requirements into technical solutions. - Facilitate business requirements sessions and conduct data analysis. - Lead the design and implementation of data engineering solutions using Microsoft Data Stack and Snowflake. - Oversee solution delivery engagements. - Architect and develop scalable data pipelines. - Implement data governance and security best practices. - Lead the design and development of Semantic Models and Reports/Dashboards. - Optimize data storage and retrieval performance. - Lead and mentor a team of data engineers and analysts. - Stay current on emerging trends and best practices in data engineering. **Qualifications Required:** - Bachelor's degree or higher in Computer Science, Information Technology, Business Administration, Engineering, or related field. - 5-8 years of experience in data engineering and data management, with 3 years in Microsoft Data Stack and/or Snowflake. - Strong experience with Azure Synapse Analytics, Azure Data Factory, Azure Data Lake, Databricks, DBT, and Snowflake. - Proficiency in data modeling, ETL/ELT processes, and designing/implementing enterprise data solutions. - Expertise in SQL and experience with Python or other programming languages for data transformation. - Strong understanding of data architecture principles, performance tuning, and security best practices. - Experience with DevOps, CI/CD pipelines, and infrastructure-as-code tools. - Excellent communication, presentation, and interpersonal skills. - Strong critical thinking and problem-solving skills. - Must be a collaborative team player and capable of working independently. You will collaborate with cross-functional teams, including data scientists, analysts, engineers, and business stakeholders, to understand requirements and translate them into scalable technical solutions. You will facilitate business requirements sessions and conduct data analysis to accurately identify and specify the data needed to support impactful business objectives. Additionally, you will lead the design and implementation of data engineering solutions using the Microsoft Data Stack (Azure Synapse, Azure Data Lake, Data Factory, Databricks, Power BI) and Snowflake. Your responsibilities will include overseeing solution delivery engagements, architecting and developing scalable data pipelines, implementing data governance, and leading the design and development of Semantic Models and Reports/Dashboards based on business requirements. You will also optimize data storage and retrieval performance, monitor health and performance metrics, troubleshoot issues, and lead and mentor a team of data engineers and analysts. **Key Responsibilities:** - Collaborate with cross-functional teams to translate requirements into technical solutions. - Facilitate business requirements sessions and conduct data analysis. - Lead the design and implementation of data engineering solutions using Microsoft Data Stack and Snowflake. - Oversee solution delivery engagements. - Architect and develop scalable data pipelines. - Implement data governance and security best practices. - Lead the design and development of Semantic Models and Reports/Dashboards. - Optimize data storage and retrieval performance. - Lead and mentor a team of data engineers and analysts. - Stay current on emerging trends and best practices in data engineering. **Qualifications Required:** - Bachelor's degree or higher in Computer Science, Information Technology, Business Administration, Engineering, or related field. - 5-8 years of experience in data engineering and data management, with 3 years in Microsoft Data Stack and/or Snowflake. - Strong experience with Azure Synapse Analytics, Azure Data Factory, Azure Data Lake, Databricks, DBT, and Snowflake. - Proficiency in data modeling, ETL/ELT processes, and designing/implementing enterprise data solutions. - Expertise in SQL a