Manager, Data Engineering & Analytics - Remote Position

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Job Description:

The Manager of Data Engineering & Analytics (Lead Data Engineer) role is organizationally under Finance & Accounting, within the Decision Support Tower. Particularly, this role will report into the Business Intelligence & Advanced Analytics space. The ideal candidate will possess a robust background in data engineering, showcasing expertise in cloud technologies, data architecture, data modeling, data integration data pipeline development.

Candidates should possess solid familiarity with data science best practices, machine learning algorithms and languages, and data visualization. The ideal candidate will increase awareness about available data and democratize access to it across the company.

As a data engineering manager, the ideal candidate will possess key technical expertise in building data assets, as well as driving a strong vision for how data engineering can proactively create a positive impact on the business. This role will enable exploration and access for analytics, visualization, machine learning, and data product development efforts across Finance.

This position will work directly with the lead data engineer and team of data scientists. The ideal candidate will connect the dots between the development environment and the project solutioning environment.

The development environment will include:

• Development of batch and real-time data pipelines utilizing various data analytics processing frameworks in support of data science, advanced analytics, machine learning and AI practices.
• Integration of data from various data sources, both internal and external.
• Extract, transform, load (ETL), data conversions, and facilitates data cleansing and enrichment.
• This position contributes to and supports synthesizing disparate data sources to create reusable and reproducible data assets.

The project solutioning environment will include:

• Lead and manage projects within the department and support leadership by planning and championing the execution of broad advanced analytics initiatives aimed at delivering value to internal and external stakeholders.
• Support the data science community working through analytical model feature tuning. 
• Work closely and collaborate with data scientists to share your passion for staying on top of tech trends, experimenting with and learning new technologies, and participate in internal and external technology communities.
• Empower the business by creating value through the increased adoption of data, data science and business intelligence landscape

RESPONSIBILITIES 

• Management of Data Engineering: Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects and strategic internal and external partners. Proactively drive impact and engagement while bringing others along. Define how we instrument, prioritize, and store data that powers AI/ML solutions
• Analytics: Apply expertise in data model development, data analytics, and data visualization tools to introduce innovative ways to answer critical business questions efficiently and effectively. Guide the team to organize the data for reporting, analytics, and data mining. 
• Data Development Lifecycle: Leads the development and design of the data engineering projects and guides the team to build solutions by leveraging a software/application solution used for statistical modeling and analysis, data warehousing and cloud solutions, and building data pipelines. Develop and optimize procedures to productionalize datasets, data models, and data science models.
• Cross-Collaboration: Collaborate with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across Finance. Recommend analytic reporting tools/technologies and leads adoption of emerging technology products and tools. 

Required Qualifications:  

• Minimum 4-5 years of experience in hands-on execution of data transformation programs, showcasing expertise in navigating data landscapes, implementing innovative solu