Manager, Data Services and Solutions

Key Skills

Aartificial intelligence, Azure, Big Data Technology, Data Analytics, Data Governance, Data Lake, Databricks, Design, KPIs, Leadership Skill, Machine learning techniques, SQL Server

Job Description

Responsibilities:

• Lead the adoption and integration of cutting-edge data technologies, including AI, machine learning, and data analytics, to enhance business intelligence, operational efficiency, data democratization, and self-service.
• Lead the design and implementation of business strategies, aligning data initiatives with organization goals, driving revenue growth, and optimizing business performance through data-driven insights.
• Subject matter expert in data warehousing, data modeling, big data, cloud infrastructure, and business intelligence tools.
• Design and build scalable data infrastructure and platforms to support enterprise-wide data needs, including data governance, data management, data quality, and data analytics.
• Drive the development and implementation of advanced analytics models to extract valuable insights from data that drive the business forward.
• Champion a data-driven culture by fostering collaboration and common data literacy across data teams and business functions.
• Foster a culture of data-driven decision-making, collaboration, and innovation.

Required Skills & Required Experience

• Design and implement cloud data solutions on Microsoft Azure, migrating on-premises data to cloud data warehouses like Azure Synapse Analytics, and Azure Databricks.
• Serve as a subject matter expert to support broader organization and stakeholder needs in developing Power BI Dashboards.
• Partner and collaborate with business stakeholders to define KPIs/metrics based on source systems, datasets, business rules, logic, and custom calculations.
• Develop Python scripts and notebooks for ETL processes, data transformations, and visualization using services like Databricks and Azure HDInsight.
• Build data pipelines to move data between various sources, such as SQL Server, Azure Data Lake Storage, and Azure Synapse SQL Pool, using tools like Azure Data Factory.
• Monitor and optimize the performance of cloud data systems using tools like Azure Monitor, Log Analytics, and Application Insights.
• Design schemas and implement ETL processes for analytical workloads in data warehouses and data lakes.

Education/Training:

• Bachelor’s degree in computer science, Information Systems, Software, or comparable field of study.
• Minimum of 10 years of related work experience.
• 5+ years of cloud data engineering experience.