Analytics Engineer

About SmartSign

Smartsign is the internet leader in physical display products. Our family of over 30 websites sells 250,000 different sign, tag and label products for offices, factories and home. We are modernizing our data foundation, analytics and AI capabilities, and are seeking a hands-on BI Lead & Data and AI Engineer to own and enhance the next-generation data environment and reporting suite that will power core decision-making, advanced analytics and AI use cases.

Role Overview

SmartSign is looking for a hybrid Analytics Engineer who can build, own and maintain our core data assets:

• The common data model and enterprise data warehouse
• Data pipelines across Azure SQL, ERPs, and third-party tools
• Standardized reporting, dashboards, and KPIs used by leadership, finance, eCommerce, marketing and operations

This is a hands-on builder role with significant influence on the company’s data future. You will take full ownership of the data warehouse, reporting suite and analytics use cases, evolving it, maintaining it, and unlocking new business value.

The ideal candidate has strong SQL and pipeline-development skills, loves wrangling complex data, and also enjoys working with business stakeholders to understand requirements, design dashboards, and translate requests into clear metrics and impactful solutions. This role is perfect for someone who wants to broaden into analytics, data science, or AI use cases over time as SmartSign expands its capabilities.

Data Engineering & Architecture

• Build and maintain scalable ETL/ELT pipelines for data ingestion, transformation, and loading from Azure SQL, ERP systems (e.g., SAP, Sage), marketing platforms, web analytics, and other sources.
• Own the common data model and ensure it evolves to support new business needs.
• Perform data modelling continually to add and map sources and maintain the model
• Maintain and optimize the enterprise data warehouse (EDW) in Snowflake or equivalent once implemented.
• Develop reproducible data transformation logic (SQL, Python) and enforce data quality.
• Manage integration of newly acquired business entity data sources to enterprise data warehouse 

Business Intelligence & Reporting

• Design and develop dashboards and self-service reporting tools (PowerBI preferred).
• Partner with finance, operations, marketing, customer service, and e-commerce teams to understand use cases and translate needs into data solutions.
• Define and standardize KPI definitions (e.g., margin, CAC, customer, manufacturing metrics, etc.).
• Create robust data models that support fast, accurate ad hoc analysis.
• Train business users on tools, dashboards, and best practices.

Data Governance & Operations

• Implement data classification, data quality, version control, security, compliance, and documentation standards.
• Monitor pipeline health, troubleshoot data issues, and ensure timely, accurate reporting.
• Work with leadership to align on process and development priorities.

Advanced Analytics & AI 

• Build descriptive and predictive analytics (e.g., pricing, forecasting, customer segmentation).
• Integrate AI/ML models, generative AI (GenAI), and autonomous agents into data workflows to enhance predictive capabilities and automate processes.
• Explore and deliver AI/ML use cases (e.g., search optimization, attribution modeling, recommendation systems).  Partner with 3^rd parties where needed.        
• Collaborate with customer service and product teams on AI-driven workflow automation.

Portfolio & Prioritization Management (PMO Light) 

• Implement a PMO framework to intake, prioritize, and track data and analytics requests.
• Maintain the data & analytics roadmap, ensuring alignment with company strategy and stakeholder needs.
• Coordinate cross-functional execution, manage dependencies, and communicate timelines and progress.
• Ensure consistency, documentation, and adoption of delivered data products and dashboards.
• Lead data integration with newly acquired businesses as appropriate

Required Qualifications

Technical Skills

• 5–8 years experience in BI, data engineering, analytics engineering, or related fields.
• Deep expertise in Microsoft SQL (Azure SQL)
• Experience building data pipelines (Python, SQL, or ETL tools).
• Experience in data modelling and data modelling tools (dbt, SQLmesh, Coalesce)
• Strong proficiency in Power BI, Tableau, or similar BI tools.
• Experience working with data warehouses (e.g., Snowflake, Azure Synapse, BigQuery) and data modeling concepts (facts/dimensions, star schema).
• Familiarity with cloud platforms (Azure preferred) and modern data stack tools (e.g., FiveTran, Stitch).
• Experience working with multiple disparate systems or messy source data.

Business & Communication Skills

• Ability to translate ambiguous business questions into clear data requirements and solutions.
• Strong stakeholder management and communication skills across technical and non-technical audiences.
• Experience organizing and defining KPIs across teams.
• Ability to manage competing priorities and run PMO process for analytics work.
• Comfort working in a fast-moving, entrepreneurial environment with partial documentation.

Bonus / Nice to Have

• Experience with e-commerce, manufacturing, or multi-site operations.
• Exposure to AI/ML, LLMs, or advanced analytics tools.
• Experience with Databricks, DBT or workflow orchestration.
• Understanding of ERP and systems and integrations (e.g., SAP B1, Dynamics, Sage, etc.).
• Understanding of CRM systems and integrations (e.g., Hubspot, Salesforce)
• Prior experience collaborating with offshore development teams.