Data Analyst

About the Company:

Stable Kernel is a technology services firm and custom software developer building scalable software solutions for cutting-edge, innovative enterprises to move their business forward. We are headquartered in Atlanta, GA. We’re a privately held, Great Place to Work Certified Company™ with multi-awards for our amazing culture. Plus we have an impressive 10+ year trajectory of sustainable growth. At Stable Kernel, we support our colleagues in ways that help them do some of the best work of their lives.

About the Role:

As a Data Analyst (DA2) at Stable Kernel you will play a key role in converting data into insights that inform client and internal product roadmaps.  Working with cross-functional teams, you will independently design dashboards, build reporting queries, and translate high-level questions into measurable metrics.  Your blend of analytical, communication and problem-solving skills will help clients evaluate how their products operate and identify opportunities for improvement. 

Data Analysts report directly to our Principal Data Strategist. 

Core Responsibilities Include:

• Technical Impact:
• Designing and building dashboards and reports that align with business objectives, using advanced features of business intelligence tools (e.g., complex SQL, calculated fields and advanced charting).
• Defining success metrics and measurement plans for new products and features
• Tracking design and data requirements, suggesting scalable and reusable solutions.
• Monitoring dashboard and data health, investigating anomalies and resolving data quality issues.
• Contributing to documentation updates and maintaining data dictionaries to ensure shared understanding across projects.
• Improving the efficiency or usability of existing reports and solutions by creating reusable queries or components and training junior analysts on tool basics.
• Collaborating with product and engineering to understand technical dependencies and translate business questions into data solutions, sharing insights during cross-functional meetings.
• Business Alignment: 
• Translating high-level client or project goals into data questions and metrics; validate that analyses align with these objectives and advise on measurement priorities.
• Providing actionable insights that inform decisions and connect analysis outcomes clearly to business KPIs, suggesting optimizations based on trends or findings.
• Breaking down analysis tasks, providing accurate estimates, and communicating expected effort and trade-offs while factoring in data complexities.
• Building a strong understanding of the client domain and user journeys, incorporating domain nuances into analyses and understanding dependencies with engineering, product and marketing processes.
• Supporting development of reusable dashboards, frameworks and templates, contribute to internal best practices and documentation, and share learnings across projects.

• Consulting:  
  • Coordinating closely with cross-functional teams to understand dependencies and identify data needs or risks early.
  • Building trust through reliable delivery and begin advising on analysis prioritization based on business impact.
  • Supporting roadmap discussions with data-backed insights, help triage competing requests and propose small enhancements where data can add value.
  • Suggesting improvements to existing metrics or frameworks and contributing to proposal or workshop preparation.
• Interacting with Others:
  • Coordinating analytics tasks with cross-functional pods, clarifying dependencies with product, design and engineering teams.
  • Supporting project planning and sprint alignment by providing clear, structured updates in stand-ups and reviews.
  • Sharing insights that inform product or marketing decisions, recommencing reporting improvements or new analyses and advising on best practices for metrics interpretation. 
  • Supporting teammates by providing tools and process guidance, proactively communicating risks and mitigation plans, documenting progress in shared tools. 
• Problem-Solving:
  • Solving moderately complex analysis challenges independently by proposing hypotheses, validating with data and recommending actionable insights.
  • Defining scope when details are unclear, suggest initial approaches to move work forward and clarify assumptions in analysis.
  • Identifying data or analysis risks and proposing mitigation steps, communicating risks clearly to project teams and escalating blockers or risks appropriately with context.
  • Documenting troubleshooting steps before escalation.
• Leadership:
  • Identifying inefficiencies in workflows within the team and suggesting and implementing process improvements.
  • Promoting data quality and consistency by encouraging adherence to standard metrics and definitions and providing guidance to junior analysts on tools and approaches.
  • Sharing knowledge in informal training and leading small analytics projects or pods, coordinating task execution and dependencies to ensure alignment on goals.

Intimate, Working Familiarity With:

• Familiarity with data warehouses, product analysis, statistical analysis tools and experience with large data sets and has managed their reliability and consistency.
• Experience with implementing and maintaining product analytics tools (such as GA4, Pendo, Amplitude) and strategy.
• Experience with app performance, analysis, app store optimization and A/B testing.
• Experience with data activation tools.
• Experience using SQL and Python.
• Experience with observability and data visualization tools such as Grafana, DataDog, Tableau, Looker or PowerBI.
• Experience using analytics-related tools such as Databricks or Amplitude.
• Familiarity with Microsoft Office Suite.

General Requirements:

• 3-5  years of experience as a data analyst.
• Experience working in a consulting or professional services organization.
• A bachelor’s degree in data analytics, data science, a quantitative/analytical field, or similar.

Nice-to-haves:

• Ability to effectively test APIs using standard tools such as Postman and curl.
• Experience using agile work management tools such as Jira.

A Bit More Info:

Minimum Base Compensation: $105,000

This is a full-time position.

Stable Kernel operates a People Before Place Hybrid model, allowing most employees to choose where they can do their best work most days.

Travel may be associated with this role as it requires you to maintain an in-office presence in a hybrid capacity for regular in-person engagements for both clients and internal teams.

Our generous total compensation package includes:

• Company-subsidized health, vision, and dental plan premium options beginning on the first day of employment
• 401k with above-average company matching 
• Fully paid Group Life, Short and Long Term Disability, and AD&D insurance
• Optional Flexible Spending Account, Dependent Care Flexible Spending Account, and Health Savings Account participation
• Voluntary Life, Critical Illness, and Accident insurance
• EAP and Health Advocacy program available at no cost to employees and their dependents
• $1500-3000 annual industry educational budget 
• Paid time off and paid holidays
• Access to Perks at Work program featuring a variety of discounted products and services

*Note - We are not sponsoring employment visas at this time. If you are currently in possession of an employment visa, it will need to be effective for at least 3 years from the date of your application for your candidacy for employment to be considered.

Stable Kernel’s culture is inclusive and expansive. We celebrate diversity in its many glorious forms and do not discriminate on the basis of race, religion, color, national origin, gender role orientation, sexual orientation, age, marital status, veteran status, or disability status.

However, we will discriminate against those unwilling to comply with the practice of our company values:

• we work with integrity always
• we respect our work and each other
• we are dedicated to life-long learning and sharing
• we stay hungry for new challenges

If you are like-minded in this regard, we hope you will apply. We look forward to meeting you.