ITS Analytics Engineering Manager - Flexible Location

Job Description

**The location of this role is flexible in areas where Avanade has an established presence**

Do you enjoy solving problems, turning data into insights and leveraging analytics to answer difficult questions, enhance business operations and decisions? So do we.

Avanade’s Information Technology Services, Intelligent Enterprise team is looking for an Analytics Engineering Manager to lead a global team of talented Analytics Engineers. This team sits alongside our operational analytics platform, working with our internal partners to build complex data models, generate Machine Learning driven predictions, improve our enterprise data platform, and modernize & enhance existing analytics solutions.

About you:

You understand and appreciate the intersection between Software Engineering best practices and data analytics products. You are an ambitious technologist who wishes to work with and contribute to the latest cloud technology from Microsoft and able to rapidly learn new technologies. You are comfortable looking after several projects at once and splitting your time between hands on development and managerial activities. You are looking for a position wherein you can meaningfully contribute today, with career growth potential for tomorrow.

Key Role Responsibilities :

• Engage with a variety of functional leaders to define and develop data driven transformation initiatives to support their business objectives
• Gather requirements through direct interaction as well as analysis of business processes and practices and translate requirements into technical solutions
• Help create strategic roadmaps to drive business outcomes that both delineate a broader endgame while also prioritizing quick wins with near-term measurable impact
• Oversee the design and the development of Data/Analytics/ML solutions and serve as technical SME
• Set the vision for the projects and manage team plans, deliverables and timelines
• Develop your team members, ensuring they deliver high quality work while growing in their careers and preparing for the next level of responsibility
• Meaningfully contribute to our ever-evolving data platform, helping to make it the best in class on the Microsoft stack, augmented with open-source libraries where applicable in order to scale our data analytics capabilities and tooling further in alignment with the high growth of the business
• Own and be accountable for the foundational data models and modern data warehouse architecture for data access and advanced analytics

Required Skills and Experience

• Motivated individual contributor and “full-stack” analyst (a.k.a. analytics engineer), with 5+ years of experience in data analysis, data engineering, data science, or analytical/quantitative roles in management consulting, finance, marketing, academia, or operations
• Strong SQL skills; experience using dbt or managing a data warehouse such as Azure Synapse, Snowflake preferred. Experience with visualization and business intelligence tools (Power BI preferred)
• Proven professional experience with data mining, analysis and modeling of large complex data sets
• Knowledge of Azure Data Factory, Azure Blob, Azure Data Lake and Azure SQL
• Experience preparing data for use in Machine Learning (Azure Machine Learning is a huge plus)
• Coding proficiency in Python is a plus
• Experience with Git/Azure DevOps including CI/CD
• Best of breed working methodologies (Agile, DevOps)
• Transforming business use cases and requirements to technical solutions
• Aptitude to define and apply strategies for Data Architecture, Data Integration, Data Modeling, Data Governance & Management, Reporting & Analytics, BI Governance, BI Self-Service
• Experience leading and managing people
• An analytical thinker looking for an opportunity to own data projects from beginning to end, with a focus on driving better results for the business
• An excellent communicator and a natural team player; curious and inquisitive and excited to gain deep knowledge of every functional area
• Bachelor’s or Master’s degree in Data Science, Computer Science or another relevant field, or an equivalent combination of education and relevant experience