Business Intelligence & Data Quality Manager

NEFCO Construction Supply LLC•East Hartford, CT

22m

About The Position

About the Role: We are looking for a rare blend: a strategic Business Intelligence leader who still loves rolling up their sleeves and fixing broken data at scale. This is not a “delegate-only” management position. You will jointly own the enterprise BI vision, roadmap, and team, while personally leading the most critical data cleanup and governance initiatives that are currently blocking trustworthy analytics. You’ll build and coach the team, but you’ll also be the go-to expert writing complex remediation SQL, defining enterprise data quality rules, and turning years of accumulated data debt into gold-standard assets.

Requirements

4+ years in business intelligence, analytics engineering, or data management
Deep hands-on expertise in at least one major BI tool
Advanced SQL mastery (complex CTEs, window functions, dynamic un-pivoting, reconciliation queries)
Strong Python for data manipulation (pandas, fuzzy matching, regex, record linkage)
Proven track record shipping large-scale data remediation projects end-to-end
Excellent stakeholder management and storytelling skills — you can explain a duplicate-key disaster to a CFO and get budget to fix it
Proven ability to find creative solutions to complex problems
Bachelor’s degree in Finance, Computer Science, Statistics, or equivalent practical experience.

Nice To Haves

Experience building and leading BI/analytics teams
Experience implementing data governance and quality frameworks from scratch
Exposure to pricing analytics, subscription metrics, or fintech/SaaS data
Familiarity with tools such as Microsoft PowerBI, Fabric, Purview, and Azure Synapse.
Relevant certifications (CDMP, DAMA, Looker LookML, dbt Analytics Engineering)

Responsibilities

Assist BI Leadership define and drive the company-wide BI strategy and prioritized roadmap in close partnership with Finance, Pricing, Sales, Marketing, Product, and Executive leadership
Assist in the selection, implementation, and continuous optimization of the BI stack (Power BI, Looker, Tableau, ThoughtSpot, Sigma, etc.) and cloud data platforms (Snowflake, BigQuery, Databricks, etc.)
Oversee data modeling, semantic layers, ETL/ELT pipelines (dbt), governance frameworks, and self-service analytics enablement
Regularly present insights, roadmap progress, and data health metrics to C-suite and Board members
Build, lead, and mentor a team of 4–8 BI analysts, analytics engineers, and data enrichment specialists (Note- this will take time. The intent is to crawl, walk, run)
Recruit top talent, conduct 1:1s, set clear goals, and create individualized career development plans
Cultivate a collaborative, high-trust, low-ego culture that prioritizes accuracy, ownership, and business impact
Personally own and execute the most complex, high-impact data cleanup and reconciliation initiatives
Perform large-scale data cleansing across CRM, ERP, billing, marketing platforms, and log data
Proactively identify and permanently resolve duplicates, missing values, legacy code mismatches, cross-system ID conflicts, orphaned records, and categorization drift
Assist with design, implement, and enforce enterprise data quality rules, automated validation pipelines, and monitoring (using tools such as Great Expectations, Monte Carlo, dbt tests, Collibra DQ, etc.)
Create and maintain the central data dictionary, business glossary, lineage documentation, and dataset quality tiers (“Trusted,” “In Remediation,” “Deprecated”)
Help establish and champion data governance policies, ownership models, and quality standards
Collaborate with business units to address root causes of poor data and deliver training on best practices
Partner with stakeholders across the organization to gather requirements, define KPIs, and translate business needs into actionable dashboards and reports
Oversee the development and maintenance of high-quality, performant, user-friendly dashboards while enforcing visualization and design standards
Drive self-service analytics adoption through certified datasets, data literacy programs, and guided analytics experiences
Bridge traditional BI with advanced analytics by collaborating with data science teams to productionize and embed predictive models
Monitor adoption and performance of BI assets; optimize queries, retire low-value reports, and continuously improve refresh times and cost efficiency
Act as the primary advocate for data-driven decision making, delivering compelling presentations and updates to leadership