Business Analytics Engineer Enterprise

Hawaiian Electric Company; Honolulu (HI); On-site; USD 123,000 - 160,000; Full time

Job summary

Hawaiian Electric Company in Honolulu, HI seeks a Business Analytics Engineer Enterprise to optimize data models and pipelines, build predictive solutions, and enable data-driven decision-making across the enterprise.

In the Enterprise Data & Analytics team, you’ll support data reliability, quality, usability, and KPI alignment, with 1 management vacancy available. Onsite role with strong analytics and data engineering focus.

Qualifications

• 7+ years of experience in data management disciplines including data integration, modeling, optimization, and data quality.

Responsibilities

• Extract knowledge and insights from high-volume, high-dimensional data using advanced statistical analysis, predictive modeling, experimentation, and pattern recognition to improve business performance.

Skills

7+ years experience

Unstructured data

Distributed computing

Agile Methodology

DevOps

PySpark

SQL

Power BI

Tableau

Databricks ML

Python/Jupyter

Education

Bachelor’s degree in data analytics / data science / computer science / MIS / business analysis / business management / engineering / finance / statistics

Tools

Azure

Databricks

Spark

SAS

Job description

Hawaiian Electric Company is seeking a Business Analytics Engineer Enterprise to support enterprise and domain analytics using data science disciplines. In this onsite role in Honolulu, HI (Oahu), you will help optimize data models and “last mile” data pipelines, build predictive and analytical solutions, and enable data-driven decision-making across the enterprise.

Within the Enterprise Data & Analytics area of the Enterprise Architecture & Planning division, you will join a professional role supporting data reliability, efficiency, quality, usability, and KPI alignment. There is 1 management vacancy available.

What you’ll do

• Extract knowledge and insights from high-volume, high-dimensional data using advanced statistical analysis, predictive modeling, experimentation, and pattern recognition to improve business performance.
• Turn existing or new models into scalable analytical solutions, creating processes for data modeling and mining and applying software engineering best practices to produce clean, transformed data for analysis.
• Support machine model development and research into new artificial intelligence applications.
• Support and/or lead timely delivery, management, enhancement, and upgrades of analytics solutions that increase business value and meet corresponding KPIs.
• Provide consulting and expertise for enterprise and domain analytics strategy by identifying opportunities to leverage data and leading direction for analytics teams and analysts as use cases are developed and delivered.
• Research opportunities for data acquisition and new uses for existing data, partnering with data subject matter experts and data science teams to determine appropriate data management systems and data needs.
• Mentor and coach employees within the department and broader organization on adoption of analytical tools, techniques, technology, information, and business intelligence usage.
• Monitor industry, functional, and technology trends and maintain multi-year data analytics plans, roadmaps, and strategy for leadership consumption.
• Remain available for both scheduled and unscheduled work, with occasional needs outside normal business hours and on weekends.
• Participate in company emergency response activities as assigned, including any actions required to prepare for emergency response.

What you bring

• 7+ years of experience in data management disciplines including data integration, modeling, optimization, and data quality, and/or related areas relevant to data engineering and analytics.
• A bachelor’s degree in data analytics, data science, computer science, management information systems, business analysis, business management, engineering, finance, statistics, or a related field (or equivalent work experience).
• Thorough knowledge of business and data analysis, including working with unstructured data, and experience supporting requirements elicitation, documentation, standardization, validation, and operations/delivery concepts.
• Understanding of distributed computing and cloud technologies with Azure experience preferred.
• Familiarity with Agile Methodology and DevOps, including experience leading cross-functional teams in a dynamic environment.
• Preferred: utility business and/or business and engineering principles and practices.
• Proficiency with key analytical tools such as PySpark (preferred), R, Python/Jupyter, SAS, Power BI, Tableau, MATLAB, and similar.
• Strong database programming fundamentals: SQL, PL/SQL, plus experience with relational databases and emerging non-relational/distributed computing tools.
• Thorough experience with data discovery, analytics, and BI software tools including Power BI and Tableau, including semantic-layer-based data discovery.
• Experience with commercial/open-source big data discovery and analysis platforms, with strong preference for Spark and Databricks ML; practical experience using Databricks for Machine Learning/Data Science is strongly preferred.
• Working knowledge of statistical methods and data mining (predictive modeling, segmentation, regression) and experience partnering with data science teams to refine and optimize models and algorithms.
• Demonstrated leadership and interpersonal skills, including effective written and oral communication and active listening across all levels and with outside contractors/consultants.
• Strong data literacy and the ability to translate business use cases into data sources, management concepts, and analytical approaches to solve complex problems with advanced analytical solutions.
• Ability to communicate complex concepts to both technical and non-technical audiences, including facilitation and storytelling/presentation techniques.
• Capability to conceptualize new ideas quickly and learn new technologies on the job, including mentoring and knowledge transfer.

Tools and technologies you may use

PySpark, R, Python, Jupyter, SAS, Power BI, Tableau, MATLAB, SQL, PL/SQL, Spark, Databricks ML, Databricks, Azure, plus Agile Methodology, DevOps, Machine Learning, Artificial intelligence, SAP, and Big Data with cloud-based architecture.

Compensation and role details

• Role: Professional
• Location: Honolulu – Oahu (onsite)
• Salary (yearly): USD 123,000 - 159,800
• Vacancies: 1 (Req ID 10761)