Product Strategy and Analytics Professional II

📍 Job Overview

Job Title: Product Strategy and Analytics Professional II

Company: Hawaii State Federal Credit Union

Location: Honolulu, Hawaii, United States

Job Type: Full-time

Category: Data Analytics & Business Intelligence / Product Strategy

Date Posted: May 01, 2026

Experience Level: Mid-Senior Level (4-6 years)

Remote Status: On-site

🚀 Role Summary

• This role is a critical hybrid position blending data engineering, data analysis, and strategic partnership within the Product Strategy and related business units.

• Focuses on designing, building, and maintaining robust datasets and data pipelines to enable reliable reporting and advanced analytics.

• Acts as a key enabler of data-driven decision-making across the organization, translating complex data into actionable insights for operational enhancement and member satisfaction.

• Requires a strong foundation in SQL, data modeling principles, and a proven ability to communicate complex findings to non-technical stakeholders.

📝 Enhancement Note: The title "Product Strategy and Analytics Professional II" suggests a role that bridges the gap between technical data capabilities and strategic business initiatives. In a "lean credit union environment," this implies a high degree of autonomy and responsibility for end-to-end data solutions. The emphasis on "Product Strategy" indicates the insights generated will directly inform product development, member offerings, and strategic planning.

📈 Primary Responsibilities

• Design, build, and maintain reusable, analytics-ready datasets and views utilizing SQL or comparable data querying and transformation tools to support product strategy and business unit needs.

• Develop and manage core data pipelines, ensuring data integrity, efficiency, and scalability for reliable reporting and advanced analytical applications.

• Collaborate closely with stakeholders in Product Strategy, Branch Operations, Consumer Lending, and other departments to understand their data requirements and translate ambiguous business questions into clear, actionable metrics and insights.

• Create and maintain dashboards and visual analytics that effectively communicate Key Performance Indicators (KPIs), trends, and insights to both technical and non-technical audiences.

• Apply core analytics concepts, including dimensional modeling and metric consistency, to ensure data accuracy and reliability for strategic decision-making.

• Identify and address data quality issues, implementing processes to improve and maintain data accuracy and trustworthiness across core datasets.

• Support advanced analytics initiatives by preparing and structuring data for statistical modeling, forecasting, and other analytical endeavors.

• Contribute to the overall data strategy of the credit union, recommending improvements to data infrastructure, tools, and processes.

📝 Enhancement Note: Given the "lean credit union environment" and the hybrid nature of the role, responsibilities will likely encompass end-to-end data lifecycle management from data acquisition and transformation to analysis and visualization. The "II" in the title suggests a level of independence and the ability to handle moderately complex projects with minimal supervision, potentially mentoring junior analysts if the team grows.

🎓 Skills & Qualifications

Education:

Experience:

Required Skills:

• SQL Proficiency: Ability to design, build, and maintain reusable, analytics-ready datasets and views using SQL or comparable data querying and transformation tools.

• Data Modeling Understanding: Knowledge of structured and relational data concepts, including tables, keys, joins, aggregations, and common data quality issues.

• Analytics-Ready Dataset Design: Understanding of principles for designing and maintaining datasets that are optimized for reusability, scalability, metric consistency, and downstream reporting needs.

• Dashboard & Visual Analytics Development: Proven skill in developing dashboards and visual analytics that clearly communicate KPIs, trends, and insights to non-technical stakeholders.

• Analytical & Problem-Solving Skills: Strong ability to evaluate data, assess alternative approaches, and recommend practical, data-driven solutions to business challenges.

• Data Quality Management: Understanding of common data quality issues and ability to implement processes to maintain data accuracy.

Preferred Skills:

• Core Analytics Concepts: Familiarity with KPIs, metrics, dimensional modeling, and the role of data in supporting operational and strategic decision-making.

• Business Acumen: Ability to translate ambiguous business questions into clear metrics, analyses, dashboards, and self-service reporting solutions.

• Banking/Credit Union Domain Knowledge: Experience working with financial data, member behavior, or product performance within a financial institution.

• Data Pipeline Concepts: Understanding of ETL/ELT processes and data pipeline design principles.

• Statistical Analysis: Basic understanding of statistical methods and their application in business analysis.

📝 Enhancement Note: The "II" level suggests that while foundational skills are required, candidates with demonstrated experience in independent project execution and a solid understanding of the business implications of their data work will be highly valued. The preference for banking experience highlights the need for domain-specific knowledge.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Data Transformation Projects: Showcase examples of building reusable datasets or views using SQL, detailing the logic, transformation steps, and the resulting data structure. Highlight how these datasets improved data accessibility or consistency.

• Dashboard & Reporting Examples: Provide samples of dashboards or visual analytics created, demonstrating clear communication of KPIs, trends, and insights. Explain the business problem addressed and the impact of the visualizations.

• Data Quality Improvement Case Studies: If possible, include examples where you identified and resolved data quality issues, detailing the process and the positive outcome.

• Problem-Solving Case Studies: Present a situation where you translated a business question into a data analysis, outlining your approach, methodologies, and the recommendations made.

Process Documentation:

• Workflow Design: Demonstrate understanding of how to document data workflows, from source to consumption, ensuring clarity and maintainability.

• Metric Definition & Governance: Experience or understanding of defining key metrics, ensuring consistency across reports, and documenting these definitions.

• Data Modeling Principles: Ability to articulate and apply principles of relational data modeling and dimensional modeling in practical applications.

📝 Enhancement Note: For this role, a portfolio demonstrating practical application of SQL for data transformation, clear visualization skills, and a logical approach to problem-solving through data will be crucial. The emphasis on "analytics-ready datasets" implies a need to showcase how data was structured for ease of use by others.

💵 Compensation & Benefits

Salary Range:

• Minimum: $57,576 USD per year

Benefits:

• Comprehensive Health Coverage: 100% coverage for medical and dental premiums for full-time employees, with 50% coverage for family members.

• Flexible Spending Plan: Pre-tax deduction options available after six months of employment.

• Generous Paid Time Off (PTO): Includes 13 paid holidays annually, Election Day, and up to 2 full days for Community Service. PTO accrual increases with years of employment.

• Retirement Savings: 401(k) plan with up to 10% employer contribution, including a 6% match and profit sharing after the first year.

• Transportation Subsidy: 100% bus pass reimbursement or up to $100 subsidy for parking and pre-tax deductions.

• Health & Wellness Programs: Access to wellness fairs, flu shot clinics, and on-site fitness centers.

• Additional Insurance: Life, accident, and disability insurance.

• Growth & Development: In-person and online training programs, workshops, career development assistance, and tuition assistance.

• Credit Union Discounts: Various discounts available to employees.

Working Hours:

• Standard full-time work week, likely 40 hours per week. The emphasis on work-life balance and "happy place" suggests a structured but supportive schedule.

📝 Enhancement Note: The salary range provided is specific and competitive for a professional role in Honolulu. The benefits package is exceptionally strong, particularly the full premium coverage for medical/dental and the generous 401(k) contributions, indicating HSFCU's commitment to employee well-being and long-term financial security. This is a significant draw for candidates.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services (Credit Union)

Company Size: The description mentions a "lean credit union environment," suggesting a mid-sized organization where roles may have broader responsibilities. LinkedIn data typically places HSFCU in the 201-500 employee range. This size fosters a close-knit, collaborative atmosphere.

Founded: Founded in 1937, Hawaii State Federal Credit Union has a long history of serving its members, indicating stability and a deep understanding of the local market.

Team Structure:

• The role supports "Product Strategy and related business units," implying close collaboration with product managers, business analysts, and potentially operations leaders.

• As a "data engineer, analyst, and strategic partner," this individual is likely a key contributor within a small, dedicated analytics or data team, or potentially a standalone role embedded within Product Strategy.

Methodology:

• Data-Driven Decision-Making: A core focus is enabling the organization to make decisions based on reliable data and actionable insights.

• Lean Operations: Emphasis on efficiency, reusability, and scalability in data solutions, likely utilizing agile principles for data development.

• Member-Centricity: Insights generated will ultimately aim to enhance member satisfaction and operational performance for members.

• Collaborative Approach: The culture values trust, encouragement, and teamwork, fostering an "ohana" (family) atmosphere.

Company Website: https://www.hawaiistatefcu.com/

📝 Enhancement Note: The credit union model emphasizes member service and community focus, which translates into a culture that values employee well-being and long-term relationships. The "lean" aspect means efficiency and resourcefulness are key, and this role is central to achieving that through data.

📈 Career & Growth Analysis

Operations Career Level: This is an "II" level professional role, typically indicating a mid-senior level requiring 4-6 years of experience. It suggests a professional who can work independently on defined projects, contribute significantly to team goals, and is developing expertise in data engineering, analytics, and product strategy support.

Reporting Structure:

• The role reports into Product Strategy or a related business intelligence/analytics function. The "strategic partner" aspect implies a close working relationship with senior stakeholders in these areas.

Operations Impact:

• The role directly impacts operational performance by providing data insights that inform strategic decisions, enhance member satisfaction, and optimize product offerings.

Growth Opportunities:

• Skill Specialization: Opportunity to deepen expertise in data engineering, advanced analytics, specific financial product data, or business intelligence tools.

• Leadership Potential: Progression to a Senior Product Strategy and Analytics Professional, or potentially a Lead Data Analyst/Engineer role, overseeing more complex projects or mentoring junior staff.

• Cross-Functional Exposure: Gaining broader business knowledge by partnering with diverse departments across the credit union.

• Continuous Learning: HSFCU actively invests in employee development through training programs, workshops, career assistance, and tuition assistance, providing clear pathways for upskilling.

📝 Enhancement Note: The "II" designation and the broad scope of responsibilities suggest this role is a significant step for an analyst looking to expand into data engineering and strategic business partnering. The company's commitment to growth and development is a strong indicator for career progression within HSFCU.

🌐 Work Environment

Office Type: On-site, full-time role located in Honolulu, Hawaii.

Office Location(s): Honolulu, Hawaii. The company's modern headquarters are mentioned, suggesting a comfortable and well-equipped workspace.

Workspace Context:

• Collaborative Environment: The culture emphasizes teamwork and an "ohana" atmosphere, indicating opportunities for interaction and knowledge sharing with colleagues.

• Technology Access: As a data-focused role, access to necessary hardware, software, and potentially specialized analytics tools is expected. The description implies a supportive environment for productivity.

• Amenities: The modern headquarters likely offers amenities that support wellness and productivity, contributing to a positive work experience.

Work Schedule:

• Standard 40-hour work week. The company culture promotes a healthy work-life balance, suggesting a predictable schedule that allows for personal time and prevents burnout.

📝 Enhancement Note: Working on-site in Honolulu offers a unique lifestyle benefit. The emphasis on a positive, collaborative, and balanced work environment is a key cultural selling point for HSFCU, particularly for those seeking stability and a strong community connection.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Likely a recruiter or HR screen to assess basic qualifications, experience, and cultural fit.

• Hiring Manager Interview: A deeper dive into your experience with SQL, data analysis, dashboarding, and your understanding of data-driven decision-making. Expect behavioral questions related to problem-solving and collaboration.

• Technical/Skills Assessment: This could involve a practical SQL test, a take-home data analysis challenge, or a case study presentation focused on building a dataset or dashboard.

• Team/Stakeholder Interviews: Meetings with potential colleagues or key stakeholders from Product Strategy or other business units to assess collaboration style and ability to communicate technical concepts.

• Final Interview: May involve senior leadership to confirm fit and discuss long-term career aspirations.

Portfolio Review Tips:

• SQL Focus: Clearly present SQL queries used for data transformation, views, and aggregations. Explain the logic and the resulting data structure.

• Visualization Clarity: Showcase dashboards that effectively communicate insights. Use clear titles, labels, and context. Be prepared to explain the business problem and the impact of your visualization.

• Problem-Solving Narrative: For case studies, structure your contribution: Problem -> Your Approach (Data/Analysis) -> Solution/Recommendations -> Impact. Quantify results whenever possible.

• Explain Your "Why": Be ready to articulate why you chose specific data structures, tools, or analytical methods, linking them back to business objectives.

• Tailor to HSFCU: If possible, research HSFCU's products and services to frame your examples within a financial services context.

Challenge Preparation:

• Data Transformation Task: Practice writing SQL queries to create derived tables or views from a sample dataset, focusing on efficiency and clarity.

• Dashboard Design: Be prepared to sketch out a dashboard for a given business scenario, identifying key metrics and visualization types.

• Business Acumen: Think about how data analysis can directly support decisions in areas like product development, member acquisition, or operational efficiency within a credit union.

📝 Enhancement Note: The "II" level role and the emphasis on translating business questions suggest that the interview process will heavily weigh problem-solving skills and the ability to connect technical work to tangible business outcomes. A well-curated portfolio is essential.

🛠 Tools & Technology Stack

Primary Tools:

• SQL: Explicitly required for data querying and transformation. This is the core technical skill.

• Data Warehousing/Database Concepts: Familiarity with relational databases and structured data is essential. Specific technologies like PostgreSQL, MySQL, or cloud-based data warehouses (e.g., Snowflake, Redshift, BigQuery) might be in use, though not explicitly stated.

• Business Intelligence (BI) Tools: Experience with dashboard development and visual analytics is required. Common tools include Tableau, Power BI, Looker, or similar platforms.

Analytics & Reporting:

• Spreadsheet Software: Proficiency in Excel or Google Sheets for ad-hoc analysis and data manipulation.

• Statistical Software (Preferred): Familiarity with tools like R or Python for more advanced statistical analysis would be beneficial but is not a strict requirement.

CRM & Automation:

• CRM Systems: While not directly mentioned, understanding how data from CRM systems (e.g., Salesforce, or a financial services-specific CRM) feeds into analytics is valuable.

• ETL/ELT Tools (Preferred): Experience with data integration and pipeline tools (e.g., Informatica, Talend, Apache Airflow, or cloud-native services) would be a plus for data engineering aspects.

📝 Enhancement Note: The emphasis is clearly on SQL and BI tools for reporting. The "data engineer" aspect suggests that while advanced ETL tools aren't explicitly listed, a strong understanding of data pipeline principles and data quality management within a data warehousing context is expected.

👥 Team Culture & Values

Operations Values:

• "Always Right By You": This core tagline reflects a commitment to member and employee well-being, integrity, and service.

• Trust & Encouragement: The company fosters a supportive environment where employees feel valued and empowered.

• Holistic Experience: Valuing the overall well-being and professional journey of employees.

• Teamwork & Collaboration: The "ohana" atmosphere emphasizes working together towards common goals.

• Data-Driven Approach: A commitment to leveraging data for informed decision-making to improve services and operations.

• Efficiency & Scalability: In a lean environment, there's an implicit value placed on creating robust, reusable, and efficient data solutions.

Collaboration Style:

• Cross-Functional Integration: Expect to work closely with various departments (Product Strategy, Branch, Lending) to gather requirements and deliver insights.

• Open Communication: The culture encourages open dialogue and feedback, essential for translating business needs into technical solutions.

• Knowledge Sharing: The "ohana" spirit suggests a willingness to share expertise and learn from colleagues.

📝 Enhancement Note: The culture at HSFCU is a significant differentiator. The emphasis on "ohana," work-life balance, and employee well-being creates a unique and attractive work environment, especially for those seeking a stable, mission-driven organization.

⚡ Challenges & Growth Opportunities

Challenges:

• Translating Ambiguity: The primary challenge will be converting loosely defined business questions from various stakeholders into concrete, measurable data requirements and analyses.

• Data Integration & Quality: In a lean environment, ensuring data consistency and quality across disparate systems can be ongoing. Building and maintaining "analytics-ready" datasets is key to mitigating this.

• Balancing Breadth and Depth: The role requires both data engineering skills (building pipelines, datasets) and analytical skills (interpreting data, creating dashboards), demanding versatility.

• Stakeholder Management: Effectively communicating complex data insights to non-technical audiences across different departments requires strong interpersonal and presentation skills.

• Resource Optimization: Working within a "lean" environment may require creative problem-solving and efficient use of available tools and resources.

Learning & Development Opportunities:

• Advanced Analytics: Opportunity to deepen skills in statistical analysis and predictive modeling by working with financial data.

• Data Engineering Best Practices: Gaining hands-on experience in designing scalable and robust data pipelines and datasets.

• Product Strategy Acumen: Developing a strong understanding of how data directly informs product development and strategic business decisions in the financial services sector.

• Cross-Departmental Expertise: Building a broad understanding of credit union operations by collaborating with various business units.

• Formal Training: HSFCU offers tuition assistance and various training programs, providing structured opportunities for upskilling.

📝 Enhancement Note: The challenges are typical for a hybrid data role in a mid-sized organization, but the growth opportunities are significant due to the company's investment in employee development and the strategic importance of the role.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you translated a vague business request into a specific data analysis. What was the outcome?" (Focus on your process: clarification, metric definition, analysis, recommendations, impact.)

• "How do you ensure data accuracy and consistency when building datasets for reporting?" (Discuss data quality checks, documentation, and validation processes.)

Company & Culture Questions:

• "Why are you interested in working for a credit union like Hawaii State Federal Credit Union?" (Highlight your understanding of the credit union model, member service, and community focus.)

• "How do you approach collaboration with non-technical stakeholders?" (Emphasize clear communication, active listening, and tailoring your message.)

Portfolio Presentation Strategy:

• Structure Your Examples: For each portfolio piece, clearly state the business problem, your role, the data/tools used, your process, the outcome, and the impact.

• Quantify Impact: Whenever possible, use numbers to demonstrate the value of your work (e.g., "improved reporting efficiency by X%", "identified Y opportunities for cost savings").

• Focus on "Analytics-Ready": For dataset examples, explain how you structured the data to make it easy for others to use for analysis and reporting.

• Be Prepared to Discuss Your Code/Logic: For SQL examples, be ready to walk through your queries and explain your design choices.

📝 Enhancement Note: The interview will likely assess both technical proficiency (SQL, BI) and the ability to apply these skills strategically within a financial services context. Strong communication and a problem-solving mindset are key.

📌 Application Steps

To apply for this Product Strategy and Analytics Professional II position:

• Submit your application through the provided Dayforce link.

• Tailor your Resume: Highlight your experience with SQL, data analysis, dashboard development, and any relevant financial services or banking experience. Quantify your achievements wherever possible.

• Prepare Your Portfolio: Curate 2-3 key projects that best showcase your skills in data transformation (SQL), dashboard creation, and problem-solving through data. Be ready to present or discuss these in detail.

• Research HSFCU: Familiarize yourself with their mission, values, products, and recent news. Understand the credit union model and what makes HSFCU unique.

• Practice Your Storytelling: Prepare to articulate how your skills and experience align with the role's responsibilities and the company's culture, particularly the "Always Right By You" ethos.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

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