Business Analytics Engineer Enterprise

Role Overview

The Business Analytics Engineer is a recognized subject matter expert in data analytics supporting the enterprise or specific domains by leading business analytics services and data-driven solutions through the data science disciplines.

What You Will Do

Extracts knowledge and insights from high volume, high dimensional data using advanced statistical analysis, algorithms, predictive modeling, experimentation and pattern recognition to create solutions that enable enhanced business performance.

Why It Might Be a Fit

Requires thorough knowledge of business and data analysis, including working with unstructured data, in support of business data requirements elicitation, documenting, standardizing, validating and thorough to extensive knowledge of operations and delivery concepts, principles, standards, tools, techniques, methodologies for data analytics to solve complex problems.

Requirements

• A bachelor’s degree in data analytics, data science, computer science, management information systems, business analysis, business management, engineering, finance, statistics, or related fields (or equivalent work experience)
• Thorough knowledge of business and data analysis, including working with unstructured data, in support of business data requirements elicitation, documenting, standardizing, validating and thorough to extensive knowledge of operations and delivery concepts, principles, standards, tools, techniques, methodologies for data analytics to solve complex problems
• Understanding of distributed computing, cloud technologies with Azure experience preferred
• Familiarity with Agile Methodology, DevOps, and experience leading cross-functional teams in a dynamic environment
• Working knowledge of utility business, business and/or engineering principles & practices preferred
• Proficiency in key analytical tools: for example, PySpark (preferred), R, Python/Jupyter, SAS, Power BI, Tableau, MATLAB, etc.
• Strong knowledge of popular database programming languages including SQL, PL/SQL, for relational databases and upcoming nonrelational databases/distributed data/computing tools
• Thorough experience working with popular data discovery, analytics and BI software tools like Power BI, Tableau, and others for semantic-layer-based data discovery
• Experience in commercial/open-source data discovery/analysis platforms for “Big Data” with preference for: Spark, Databricks ML, with thorough knowledge and practical experience using Databricks for Machine Learning/Data Science strongly preferred
• Working knowledge of statistical methods and data mining techniques (predictive modeling, segmentation, regression, etc.) and experience in working with data science teams in refining and optimizing data science and machine learning models and algorithms
• Demonstrated leadership and interpersonal skills (effective written, oral and listening communication) in order to work effectively with all levels of the company and with outside contractors and consultants
• Demonstrated strong analytical skills and thorough Data Literacy with the ability to describe business use cases/outcomes, data sources and management concepts, analytical approaches/options and solve business problems with advanced analytical solutions
• Ability to communicate complex information to technical and non-technical audiences, facilitate multi-level briefings and superior presentation skills, including storytelling and other techniques to guide and inspire
• Ability to conceptualize new ideas quickly and ability to learn new technologies on the job
• Communicates difficult concepts and negotiate adoption of new perspectives across the enterprise while mentoring teams and facilitating knowledge transfer
• Extensive (7+ or more) years experience in data management disciplines including data integration, modeling, optimization, and data quality, and/or other areas directly relevant to data engineering and analytics
• Several (3-5) years experience with project management, working in cross-functional teams with business stakeholders, in support of multi-departmental data management and analytics initiatives is preferred

Benefits

• Dental insurance
• Vision insurance
• Health insurance
• 401(k) or other retirement plan
• Paid time off
• Life insurance
• Disability insurance

Tagged as: Data Analysis, Power BI, Project Management, Python, SQL