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Stable Kernel · 9 hours ago

Data Analyst

Atlanta, GA

Full-time

Hybrid

Mid Level

3+ years exp

Stable Kernel is a technology services firm and custom software developer building scalable software solutions. As a Data Analyst, you will convert data into insights, design dashboards, and collaborate with cross-functional teams to inform product roadmaps and improve client offerings.

Artificial Intelligence (AI)Consumer SoftwareData IntegrationData VisualizationEnterprise SoftwareMachine LearningMobile AppsMobile PaymentsSoftware EngineeringUsability Testing

Comp. & Benefits

No H1B

Responsibilities

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

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, provide accurate estimates, and communicate 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

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 contribute to proposal or workshop preparation

Coordinating analytics tasks within 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, recommending reporting improvements or new analyses and advising on best practices for metrics interpretation

Supporting teammates by providing tool and process guidance, proactively communicating risks and mitigation plans, and documenting progress in shared tools

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 propose mitigation steps, communicating risks clearly to project teams and escalating blockers or risks appropriately with context

Documenting troubleshooting steps before escalation

Identifying inefficiencies in workflows within the team and suggest and implement 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 trainings or code reviews and lead small analytics projects or pods, coordinating task execution and dependencies to ensure alignment on goals

Qualification

SQLPythonData visualizationData warehousesCRM toolsStatistical analysisAgile methodologyProblem-solvingCommunicationTeam collaboration

Required

3-5 years of experience as a data analyst

Experience working in a consulting or professional services organization

A bachelor's degree in data science, a quantitative/analytical field, or similar

Familiarity with data warehouses, product analysis, statistical analysis tools and experience with large data sets and has managed their reliability and consistency

Experience with CRM tools such as MoEngage

Experience with data activation tools such as Hightouch

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