Senior Analytics Engineer

Basic Function: This is a hands-on build-and-own role, not a coordination role. The Senior Analytics Engineer will take direct ownership of data ingestion, modeling, and governance work that is currently outsourced or distributed across an MSP, a project-based BI consultant, and prior internal contributors whose work was never unified under one owner. The role will begin by working closely alongside the interim PE-firm analytics resource to ensure continuity, then transition fully into ownership of the function as the backfill is completed.

Essential Functions:

·        Evaluate and recommend a modern data Warehouse/Lakehouse platform (e.g., Microsoft Fabric, Snowflake, Azure Synapse, Databricks, or similar), then design, build, and maintain that architecture, replacing the current reliance on external MSP-managed infrastructure.

·        Own end-to-end ETL/ELT pipelines from source systems (Sage 100, Acumatica, Quick Books and other entity-level ERPs, plus ancillary systems) into a governed warehouse.

·        Establish and enforce data modeling standards (e.g., dimensional/star schema design) to replace inconsistent, duplicated, and conflicting table structures inherited from multiple prior contributors.

·        Build and maintain a data governance framework: definitions, naming conventions, data quality rules, access controls, and lineage documentation, so that metrics are consistent and trustworthy across business units.

·        Consolidate reporting onto Power BI as the company standard, sunsetting redundant report servers, shadow tools, and one-off Excel/Access-based reporting.

·        Manage data access and security models within the new architecture, replacing ad hoc or MSP-controlled access provisioning with a structured, auditable approach.

·        Work alongside the interim PE-firm analytics resource during the transition period to absorb existing reporting logic, data definitions, and stakeholder context, then assume full ownership of the function.

·        Partner with a project-based Power BI consultant and business stakeholders to translate reporting needs into governed, reusable data models rather than one-off reports.

·        Support integration of newly acquired entities into the unified data architecture as part of the company’s ongoing acquisition strategy.

·        Document data architecture, pipelines, and governance policies to support audit readiness and reduce key-person dependency.

Required Skills

·        5 years of experience in data/analytics engineering, with direct, hands-on experience designing and building data Warehouses or Lakehouse on one or more modern platforms (e.g., Microsoft Fabric, Snowflake, Azure Synapse, Databricks, or similar).

·        Strong ETL/ELT development experience — building and maintaining pipelines from multiple source systems, including ERP platforms.

·        Solid grounding in data modeling principles (dimensional modeling, normalization/denormalization tradeoffs, slowly changing dimensions).

·        Demonstrated experience implementing data governance practices: data quality, access control, documentation, and lineage.

·        Strong Power BI development skills (data modeling, DAX, report/dashboard design) sufficient to set enterprise standards, not just build individual reports.

·        Experience working with or migrating away from MSP-managed infrastructure or otherwise transitioning outsourced technical functions in-house.

·        Comfortable working in a multi-entity, multi-ERP environment with inconsistent legacy data (duplicate records, inconsistent coding structures, etc.).

·        Strong collaboration skills and the ability to work effectively alongside an interim/transitional resource during a knowledge-transfer period.

·        Ability to objectively evaluate competing data platform options against the company’s scale, budget, and multi-entity/multi-ERP complexity, and make a clear, well-reasoned recommendation.

Preferred Skills:

·        Experience with Sage 100 and/or Acumatica as source systems.

·        Experience in a PE-backed or acquisition-driven company, where systems consolidation and “clean for diligence” data practices matter.

·        Advanced SQL proficiency; familiarity with Python or other scripting for pipeline automation.

·        Prior experience standing up a net-new data architecture from a fragmented starting point, rather than maintaining an existing mature one.

W.S. Connelly & Co., LLC (WSC) is an Equal Opportunity Employer. WSC does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.