Data Intelligence & Reporting Lead

Role Description

We are looking for a Data Intelligence & Reporting Lead to own data quality, reporting structure, signal standardization, and decision-ready intelligence across a fast-moving tech and operations environment. In this role, you won't just be building reports—you will turn messy operational data into trusted reporting, governed metrics, actionable signals, predictive insights, and automated workflows. You are someone who naturally challenges data assumptions, defines key metric definitions, and enables teams to make smarter, faster decisions.

Note: This is a data intelligence, reporting architecture, and signal governance role. It is not a basic data-entry or Excel-only reporting position.

What You Will Own

• Data Integrity: Clean, validate, normalize, and boost the reliability of business data; identify duplicated or inconsistent data before it impacts key decisions.
• Reporting Architecture: Design repeatable reporting structures, interactive dashboards, and report-ready data packets while automating manual reporting.
• Signal & Tag Standardization: Establish clear, unified definitions for tags, signals, categories, and operational events to ensure alignment across all teams.
• Predictive Intelligence: Uncover patterns, risk indicators, and growth opportunities in operational data to shift reporting from hindsight to forward-looking decision support.
• A/B Testing & Experimentation: Support statistically sound experiments (sample size, confidence, and decision rules) so teams know when results are truly meaningful.
• Anonymized Insight Packaging: Prepare aggregated, privacy-compliant insight outputs to safely leverage commercial data opportunities.

Key Responsibilities

• Maintain data quality reviews across dashboards, reports, tags, and core business metrics.
• Build and maintain a comprehensive data dictionary for key metrics and operational fields.
• Design BI dashboards, automated reports, and streamlined reporting workflows for leadership and operational teams.
• Standardize tag and signal definitions across tools, customer intelligence, marketing campaigns, calls, and market activity.
• Design structured A/B testing frameworks (hypotheses, variants, timelines, statistical significance).
• Responsibly leverage LLM/AI tools to accelerate analysis, summaries, and documentation without sacrificing accuracy or governance.
• Collaboratively challenge unclear data assumptions and work across technical, finance, operations, and growth teams.

What We Are Looking For

Required Skills:

• Data Analysis & Spreadsheets: Strong background in cleaning, analyzing, and explaining operational/commercial data using Excel/Google Sheets (pivots, formulas, structured reporting).
• BI & SQL: Hands-on experience with modern BI tools and SQL/querying to retrieve and validate source data.
• Statistics & Experimentation: Solid understanding of sample sizes, variance, confidence intervals, and experiment design.
• Data Governance & Automation: Proven ability to manage metric dictionaries, build sources of truth, and automate repetitive reporting steps.
• LLM-Assisted Workflows: Comfortable using AI tools as force multipliers for QA, documentation, and analysis.
• Stakeholder Communication: Ability to translate complex data findings into simple, actionable insights for non-technical leadership.

Preferred Background & Experience:

• Experience in Fintech, Insurtech, SaaS, Marketplaces, or Revenue Operations.
• Familiarity with Python/R, ETL pipelines, data warehouses, CRMs, or APIs.
• Experience in conversion funnel optimization, campaign testing, or data privacy/anonymization standards.

What Success Looks Like (First 90 Days)

• First 30 Days: Audit existing data sources, Excel workflows, and reporting pain points; deliver an initial data audit and quick-win automation plan.
• First 60 Days: Establish the foundational data dictionary, core KPI definitions, and tag taxonomy; launch initial reporting architecture improvements.
• First 90 Days: Operationalize automated data quality checks, improve reporting speed, and support cross-functional decision-making through standard metrics and experiments.

Mindset We Value

• Curious & Skeptical: You question weak assumptions and check what’s missing.
• Structured: You turn vague requests into clear definitions, reports, and action items.
• LLM-First & Modern: You use AI and automation to scale your impact while maintaining strict governance.
• Business-Aware: You know data exists to drive operations, customer outcomes, and revenue.

How to Apply

If you thrive in high-speed technology environments, love building clean data architecture, and want to shape how decisions are made, we’d love to hear from you! Apply directly with your updated resume and portfolio/examples of past BI or analytics work.