Lovesac is a fast-growing furniture company dedicated to creating adaptable and sustainable furniture solutions. The Sr. Engineer, Data & Analytics will build the data foundation and analytics solutions, designing and scaling pipelines and Power BI dashboards to provide actionable insights across the business.
Responsibilities:
- Design, develop, and maintain scalable, high-performance Power BI dashboards, reports, and apps aligned to business needs
- Build and optimize Power BI semantic models, leveraging best practices in data modeling, DAX, and performance tuning
- Translate complex business questions into intuitive, easy-to-use visualizations that drive insight and action
- Partner with stakeholders to define requirements, success metrics, and reporting standards
- Design, build, and maintain scalable data ingestion and ETL/ELT pipelines in Microsoft Fabric (Data Factory pipelines, Dataflows Gen2, and Spark notebooks) to land data from source systems into OneLake
- Develop and optimize Lakehouse and Warehouse solutions in Fabric, applying a medallion (bronze/silver/gold) architecture with Delta/Parquet to produce clean, reliable, analytics-ready data
- Write efficient transformation logic in SQL, Python, and PySpark, and tune Spark and warehouse workloads for performance and cost
- Orchestrate, schedule, and monitor pipelines end-to-end, building proactive alerting and error handling so data-refresh failures are caught and resolved before they reach the business
- Connect the engineering layer directly to Power BI using Direct Lake and well-structured star schemas, minimizing data movement and duplication
- Own and shape source data models, ETL/ELT logic, and data pipelines—partnering with Platform and Data Engineering—to support reliable, governed reporting
- Ensure analytics solutions are built on clean, well-structured, and governed data
- Identify opportunities to improve data quality, usability, and scalability across reporting layers
- Establish governed, reusable data products in OneLake that serve as a single source of truth across Power BI and downstream analytics
- Act as a trusted analytics partner to business teams, guiding them on how to interpret and use insights effectively
- Ensure dashboards and reports are actionable, clearly documented, and optimized for ongoing adoption
- Embed insights into day-to-day decision-making across corporate and field teams
- Establish and follow Power BI standards for modeling, visualization, performance, and security
- Implement row-level security (RLS) and follow data privacy and governance requirements
- Maintain consistent definitions, metrics, and reporting logic to ensure a single source of truth
- Apply source control and CI/CD using Git integration and Fabric deployment pipelines to promote changes safely across development, test, and production
- Manage workspace access, sensitivity labels, and data governance across Fabric and Power BI (e.g., Microsoft Purview) to keep data secure and compliant
- Stay current on Power BI, Microsoft Fabric, and analytics best practices
- Identify opportunities to enhance existing dashboards, automate reporting, and introduce advanced analytics capabilities
- Serve as a technical mentor and thought partner to others across analytics and data teams
- Ensure analytics solutions drive measurable business impact, adoption, and decision quality
- Track usage, performance, and effectiveness of dashboards to continuously improve value delivery
- Partner with stakeholders to ensure insights translate into meaningful action
Requirements:
- Bachelor's degree in Computer Science, Data Science, Engineering, Analytics or related field required
- 5+ years of experience across data engineering and analytics/BI, with hands-on expertise in Power BI and in building production data pipelines
- Strong experience delivering data and AI solutions that drive business outcomes
- Proven experience using Power BI platforms, driving scalable analytics and enterprise insights
- Advanced experience with DAX, data modeling, performance optimization, and visualization best practices
- Strong SQL skills and experience working with modern data platforms (e.g., Microsoft Fabric, Azure, Snowflake, Databricks, Redshift, BigQuery)
- Hands-on experience with Microsoft Fabric—OneLake, Lakehouse, Warehouse, Data Factory pipelines, Dataflows Gen2, Notebooks, and Direct Lake—or an equivalent modern data engineering stack
- Proven data engineering experience designing, building, and orchestrating ETL/ELT pipelines and data ingestion at scale
- Proficiency in Python and PySpark (or Spark SQL) for large-scale data transformation
- Experience with a lakehouse/medallion architecture (bronze/silver/gold) and Delta Lake/Parquet
- Familiarity with Git-based source control and CI/CD or deployment pipelines for analytics and data assets
- Experience partnering with business leaders to deliver analytics that drive business decisions
- Strong communication skills with the ability to translate technical concepts into business-friendly insights
- Self-directed, curious, and driven by continuous improvement
- Must be able to travel using various forms of transportation, as required by the Company in its sole discretion, for mandatory meetings and conferences held either at our offices or off-site (i.e. quarterly team connection weeks, companywide meetings and events, vendor visits)
- Must comply with all policies and procedures outlined in the Lovesac Employee Handbook and work collaboratively with fellow employees, treating all clients, both internal and external with dignity and respect at all times
- Experience in furniture, home goods, lifestyle, or other high-consideration consumer categories