Senior Data Analyst

Stable Kernel • Atlanta, GA

4d • Hybrid

About The Position

The Senior Data Analyst aggregates and analyzes client data to derive insights and recommendations for business optimization, communicating recommendations to clients and supporting teams. The role partners with client product owners to assess whether products and projects operate as intended and solve business problems. On data migration engagements, the analyst works alongside data engineers to validate, specify, and prove the migration of reporting and data assets to modern cloud platforms. The position reports directly to the Director of Data Strategy.

The role combines advanced analytics, consulting, product and business alignment, stakeholder communication, problem-solving, and team leadership. It includes designing measurement frameworks, shaping analytics strategies and workflows, advising clients and executives, guiding roadmap and backlog discussions, leading discovery and problem-solving sessions, and mentoring colleagues. The analyst also supports client growth and statements of work.

For data migration delivery, the analyst validates reporting and data assets, confirms ownership and usage, reverse-engineers and documents business logic, proves parity between legacy and target environments, runs reconciliation checks, supports parallel runs and cutovers, defines gold-layer requirements and data quality rules, and conducts consumer interviews, user acceptance testing, and training.

Stable Kernel is a technology services firm and custom software developer headquartered in Atlanta, Georgia. The company uses a People Before Place hybrid model, allowing most employees to choose where they work most days. This role requires an in-office presence for regular in-person client and internal engagements, and travel may be associated with the position.

Requirements

• 5–8 years of experience as a data analyst.
• Experience working in a consulting or professional services organization.
• Experience supporting a data migration or platform modernization project, including source-to-target mapping and validation of migrated data.
• Bachelor’s degree in data science, a quantitative or analytical field, or a similar field.
• Familiarity with data warehouses, product analysis, statistical analysis tools, and large data sets, including managing data reliability and consistency.
• Experience with Customer Engagement Platform RM tools such as MoEngage or Braze.
• Experience with reverse ETL and tools such as Hightouch.
• Experience using SQL and Python.
• Experience with Databricks and medallion architecture data models, or comparable lakehouse platforms.
• Experience with observability and BI tools such as DataDog, Anomalo, Tableau, Cognos, Looker, or PowerBI.
• Experience using implementation and analytics tools such as Google Tag Manager, Google Analytics, Pendo, or Amplitude.
• Familiarity with Microsoft Office Suite.

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.

Responsibilities

• Aggregate and analyze client data to derive business optimization insights and recommendations, and communicate findings to clients and supporting teams.
• Design and implement solutions that support product and team growth, improve future work speed, and preserve flexibility without unnecessary complexity.
• Own end-to-end measurement frameworks for complex data structures and drive standardization across projects.
• Lead advanced analytics strategies based on data-driven insights and craft reusable solutions and workflows.
• Evaluate and recommend analytics tooling and platforms for adoption across teams.
• Apply an understanding of cross-department practices, products, and infrastructure, and advocate for data considerations in product and strategy discussions.
• Bridge communication gaps among business, engineering, and executive stakeholders.
• Understand client business goals, refine business questions, align team efforts with long-term goals, and identify underlying needs and opportunities.
• Facilitate team discussions to identify gaps, risks, and assumptions and support accurate work estimates.
• Identify organic client growth opportunities, engage clients on next steps, and support statements of work by independently crafting sections related to data capabilities.
• Coordinate and lead analytics initiatives with stakeholders outside the team, including product and design leadership.
• Influence strategic decisions, guide roadmap discussions with data-backed perspectives, advise stakeholders across the VP-level organization, and deliver strategic status and team reports.
• Act as a subject matter expert in high-level client discussions and champion analytics solutions and service offerings.
• Prioritize data-led initiatives with clients, represent their needs in planning sessions, and plan and execute complex work with limited input.
• Shape problem definitions, measurement frameworks, and business goals; lead discovery sessions that inform product roadmaps and data-founded decisions.
• Identify and solve complex, high-priority problems; develop short- and long-term solutions; and use end-user and client goals to inform product direction.
• Lead problem-solving workshops, mitigate risks and roadblocks, anticipate future risks, develop contingency plans, and independently navigate difficult situations or escalate with a proposed solution.
• Own internal projects that streamline team processes and drive best practices across projects and client programs.
• Mentor and guide junior and intermediate colleagues, provide constructive feedback, lead team learning sessions, resolve conflicts, and support professional growth.
• Demonstrate product leadership by planning, delegating, monitoring progress, making critical decisions, and driving deliverables to successful implementation.
• Represent the team in client conversations.
• Validate existing reporting and data consumption assets before migration, reviewing metadata repositories and usage data to confirm ownership, consumers, and source systems.
• Reverse-engineer business logic embedded in BI tools and document it as business rules for confirmation by client owners.
• Prove parity between legacy and target environments, define and run reconciliation checks, and assemble evidence for client sign-off.
• Support extended parallel runs for finance and SOX-related reporting with finance and audit stakeholders.
• Partner with client Data Product Owners and business users through cutover.
• Define gold-layer requirements, data contracts, and data quality rules with Data Product Owners.
• Conduct consumer interviews, user acceptance testing, and support training for migrated reports and dashboards.

Benefits

• Company-subsidized health, vision, and dental plan premium options beginning on the first day of employment.
• 401(k) 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.
• Employee Assistance Program and Health Advocacy program available at no cost to employees and their dependents.
• $1,500–$3,000 annual industry educational budget.
• Paid time off and paid holidays.
• Perks at Work program featuring discounted products and services.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior