• Deliver client-specific analytics solutions: Use Ursa Studio to develop, implement, and maintain Synthetic Objects, Data Marts, and measures tailored to client needs that enable rapid insight and drive operational and clinical impact. • Partner with Customer Success: Collaborate with Technical Customer Success Managers and leadership to scope, plan, manage, and support analytics engineering workstreams with clients, including multi-month embedded engagements and ad hoc initiatives. • Consult and train clients: Provide hands-off-keyboard expertise in analytics engineering using Ursa Studio, including technical scoping, advisory consulting, and training on best-practice analytics workflows using Ursa’s platform. • Effectively balance being responsive to client requests with building better solutions based on our experience and expertise. • Contribute to Ursa product/cross-client solutions: Build scalable, high-impact data models and analytics components that enhance Ursa's SaaS platform and marketplace, making powerful analytic tools accessible to all clients. • Thoughtfully work with AI-assisted tooling: Leverage AI tools (including internally developed Ursa Compass) and capabilities to accelerate and improve our delivery approach, appropriately apply the domain knowledge and human intelligence to ensure sound output. • Ensure high-quality written and verbal communication: Clearly document solution approaches and final deliverables for both technical and non-technical stakeholders. • Maintain standards and security: Stay current with healthcare data regulations and Ursa’s privacy and security policies, including HIPAA compliance.

• Develop and maintain ETL processes using Informatica PowerCenter and related components. • Create, maintain, and optimize stored procedures, functions, inline SQL, and other database-driven processes. • Monitor, support, and troubleshoot applications utilizing technologies such as Informatica and Greenplum. • Work during production maintenance windows and participate in on‑call support as needed. • Participate independently in all phases of the Agile Software Development Life Cycle.

• Prepare technical architecture and design documents; • Develop data modeling; • Manage the Databricks environment; • Manage AWS, Azure and GCP cloud components; • Develop solutions using (Java / Python / Spark / Scala); • Configure network components in hybrid environments; • Define best practices for relational and non-relational data storage; • Implement improvements in Data Lake and Data Warehouse environments; • Implement and manage SQL and NoSQL databases; • Define and develop DevOps, Docker and Kubernetes solutions; • Discuss and define the best solutions for system integrations; • Support the creation of data governance processes; • Advise on the best solutions to support the company's self-service BI strategy.

Role Description FableticsOS is looking for a Senior Data Analytics Engineer to strengthen the data foundations of our Global Supply Chain and Merchandise Planning domains. You will model and build the data that powers how we move product around the world and decide what to make and buy — connecting logistics, sourcing, ERP, and planning systems into trusted, reusable data products. As a Senior Data Analytics Engineer, you will design and build scalable, high-quality data models and pipelines that support our supply chain and merchandise planning organizations. You'll lead technical design, establish engineering standards, and deliver analytical data products end-to-end—from discovery and architecture through implementation. Partnering closely with planning, sourcing, logistics, and commercial teams, you'll translate business needs into data solutions that improve planning, forecasting, and operational decision-making. This role focuses on two primary domains: - Logistics & Supply Chain Visibility: Integrate ETA, transit, freight, and landed-cost data from logistics platforms into Snowflake, combining it with PLM, ERP, and planning data to improve purchase order planning and visibility. - Planning Platform Data Architecture: Own the data feeds and integrations that power our supply chain and merchandise planning platform, ensuring data integrity while supporting expansion into assortment, production, and capacity planning. Supporting both areas is a strong foundation in our enterprise data warehouse (EDW), including core models, standards, and architectural principles that underpin all analytics and data engineering work across the organization. Qualifications - 6+ years of experience in a data or software-adjacent field, working with systems and data infrastructure at scale. - Experience designing and implementing mature data pipelines across a data lake and Enterprise Data Warehouse (EDW), using Dimensional (Kimball) modeling methodologies. - Experience integrating data across fragmented or disparate source systems into coherent, reliable data products. - Experience with ELT/ETL tooling and workflow orchestration (e.g., Apache Airflow). - Strong experience with relational databases and SQL in an analytical context. - Experience with data exploration, visualization, and data storytelling. - Excellent written and spoken communication, with a proven ability to work with a wide range of both technical and non-technical stakeholders. - Highly skilled at writing and maintaining high-quality, reusable code, applying design patterns and meeting coding standards. - A pragmatic adopter of AI in your own work — you use LLMs and AI-assisted tooling to accelerate development, code review, documentation, and data exploration, with good judgment about where they help and where they don't. - Track record of independently owning complex, ambiguous data initiatives end-to-end — making the architectural decisions, setting standards, and influencing technical direction across teams. - Experience with Snowflake, Airflow and Tableau is preferred. Requirements - Integrate logistics and planning data: Bring logistics visibility data (ETAs, transit times) into Snowflake and connect it with PLM, ERP, and planning sources for accurate PO loading and freight/landed-cost estimates. - Build trusted, reusable data products: Connect disparate supply chain and merchandising datasets into curated data products across our data lake and EDW, with reliable, well-defined metrics that power self-serve analytics across teams. - Own data quality and integration integrity: Take ownership of data quality across fragmented upstream systems — building the monitoring and controls that keep critical feeds reliable and integrations healthy as the planning landscape evolves. - Model data using best practices: Apply established Data Warehousing methodologies, primarily Dimensional (Kimball) modeling. - Turn complexity into insight: Transform large, complex datasets into actionable insights, delivered in a consumable format for historical and predictive analysis. - Perform data governance: Handle technical stewardship, data classification, compliance, and security considerations. - Validate before release: Build data visualizations to trial and validate data products before releasing them to customers. Benefits - Hybrid Work Schedule* - Discretionary Paid Time Off* - Summer Fridays* - Healthcare Plans - Employee Discounts - 401k - Annual Bonus Program - Equity Program* - And More *Varied for retail, fulfillment and fully remote roles. The annual base salary range for this position is from $120,000-$140,000. The range provided includes the base salary that FableticsOS expects to pay for the role. Offered base salary will be dependent on factors including the scope and complexity of the role, candidate’s related work experience, subject matter expertise and work location.