Manager, Data Engineering and Analytics Naperville, IL
About The Position
client that is seeking a Manager, Data Engineering and Analytics in Naperville, IL. Key Tasks: Owns the Solution Architecture and ensures best practices and internal processes are followed when solutions are designed and implemented Create and own standards and templates to streamline the data pipelines and engineering processes Collaborate with cross-functional teams for effective management of the Data and Analytics environment Lead engineering teams in timely delivery of products working closely with product and stakeholders Manage identification of data sources, provide data flow diagrams, and document source to target mapping and process Effectively lead and collaborate with engineering and database teams respectively to manage the data warehouse performance by optimizing batch processing through parallelization, performance tuning, aggregations, etc. Recognize and adopt best practices in developing analytical insights including data integrity, analysis, test design, validation, and documentation Proactively promotes data quality and security through recommended approaches and practices Create a collaborative environment where different of option is valued and encouraged Provide guidance and mentor team members Keep up with current with data trends and technological innovations Execute on POC's with new technologies, drive innovation, and new ideas Other duties as assigned
Requirements
- Bachelor's degree in Computer Science or related discipline or equivalent field
- 10+ years of direct experience using databases, including Oracle, MySQL, SQL Server, or Redshift
- 10+ years of hands-on experience developing with SQL, PL/SQL, SSIS, SSAS (Tabular), Power BI
- 10+ years of Cloud architecture experience, preferably in AWS (Azure or Google will also be considered) with expertise in Python, Pyspark, Glue, Athena, Lamdas and Step Functions
- Strong experience in Power Automate Architecture
- Ability and experience in leading teams
- Strong experience with business intelligence and data warehousing design principles and industry best practices including multi-dimensional modelling (star schemas, snowflakes, de-normalized models, handling -slow-changing- dimensions)
- Experience with automation using but not limited to Java, C#, Python, Pyspark
- Strong understanding data modeling (i.e. conceptual, logical and physical model design, experience with Operation Data Stores, Enterprise Data warehouses and Data Marts)
- Expert knowledge on T-SQL/DAX, Python, and microservice/cloud architectures/pipelines
- Knowledge of modern development techniques: Agile (Scrum, Kanban)
- Effective problem-solving and analytical skills; Ability to manage and prioritize multiple projects and report simultaneously across different stakeholders
- Strong communication skills, both verbally, and written
- Strong work ethic and ability to work in a dynamic environment
- Empathetic leader with leadership skills
- Ability to learn and apply new technologies to business problems
- Ability to learn and adapt quickly to changing data landscape
- Ability to work on multiple projects and tasks with overlapping time frames and facilitate construction of 90-day forecast
Responsibilities
- Owns the Solution Architecture and ensures best practices and internal processes are followed when solutions are designed and implemented
- Create and own standards and templates to streamline the data pipelines and engineering processes
- Collaborate with cross-functional teams for effective management of the Data and Analytics environment
- Lead engineering teams in timely delivery of products working closely with product and stakeholders
- Manage identification of data sources, provide data flow diagrams, and document source to target mapping and process
- Effectively lead and collaborate with engineering and database teams respectively to manage the data warehouse performance by optimizing batch processing through parallelization, performance tuning, aggregations, etc.
- Recognize and adopt best practices in developing analytical insights including data integrity, analysis, test design, validation, and documentation
- Proactively promotes data quality and security through recommended approaches and practices
- Create a collaborative environment where different of option is valued and encouraged
- Provide guidance and mentor team members
- Keep up with current with data trends and technological innovations
- Execute on POC's with new technologies, drive innovation, and new ideas
- Other duties as assigned
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What This Job Offers
Job Type
Full-time
Career Level
Manager
