Business Analytics Engineer Enterprise - Oahu

Hawaiian Electric•Kailua, HI

4d•$123,000 - $159,800•Onsite

About The Position

The P EB ENTERPRISE DATA & ANALYTICS Department of the P ENTERPRISE ARCHITECTURE & PLANNING Division at Hawaiian Electric Company has 1 Management vacancy available. (Role: Professional) 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. These roles focus on optimizing data models, business aggregate (“last mile”) data pipelines and leveraging data as a strategic enterprise asset to enhance business performance, process effectiveness, predict outcomes and develop business intelligence to support data driven decisions. These roles are able to tell the story of data, evangelize good data usage, advise, and teach while transforming data into information, information into insight and insight into business actions. Specific functional domain expertise may be required: This position works across all functional data domains and enterprise-wide across Hawaiian Electric Company, Hawaii Electric Light Company and Maui Electric Company (the Companies).

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) is required.
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.
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.

Nice To Haves

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.
Electric utility experience and Azure, Databricks, SAP, Big Data, Cloud based architecture experience is desirable.
Data Analytics/product or industry certification is desired.

Responsibilities

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.
Converts existing or new models into scalable analytical solutions and creates processes for data modeling, mining, and production and applies software engineering best practices to analytics code to provide clean, transformed data ready for analysis.
Provides support for developing machine models and research into new artificial intelligence applications.
Supports and/or leads the Companies to timely deliver, manage, enhance and upgrade analytical solutions that increase business value, improve data reliability, efficiency, quality, useability and meet corresponding key performance indicators (KPIs).
Provides consulting and expertise for enterprise or domain specific strategy to understand business priorities, identify opportunities to leverage data, and provides leadership and direction to analytics teams and/or analysts to promote awareness and potential of the value proposition as use cases are developed and delivered.
Researches opportunities for data acquisition and new uses for existing data, understands and identifies applications of data to the operation of the business, and work closely with data subject matter experts and data science teams to determine what data management systems are appropriate and what data is needed.
Mentors and coaches employees within the department, in the data analytics community (such as data scientists, data analysts, business users or any data consumers), and across the organization in the adoption of new analytical tools, techniques, technology, information and in the use of business intelligence tools to enhance business decision-making capability.
Proactively monitors industry, functional, and technology trends, guiding business partners on emerging opportunities and new technology/product development and maintains multi-year data analytic plans, roadmaps and strategy for leadership consumption.
Remain available for both scheduled and unscheduled work. Said work is occasionally required outside normal business hours and on weekends.
Participates in Company emergency response activities as assigned, including any activities required to prepare for such emergency response.