Top Data & Analytics Jobs

Own the end-to-end architecture of Opiniion’s data platform, including ingestion, transformation, storage, modeling, governance, semantic layers, and BI/AI enablement. Partner with software architecture leadership on a new platform, guide migration decisions, establish data quality and lineage practices, design statistical models, and mentor data engineers. The role requires hands-on expertise with Databricks, modern data modeling, ETL/ELT orchestration, distributed processing, cloud infrastructure, and AI/ML data readiness.

The Data Analyst will lead end-to-end analytics, develop metrics and dashboards, automate reporting and data-quality checks, and build lightweight scoring, classification, similarity, and risk-adjustment models. The role partners with Sales, Operations, Product, and leadership to answer ambiguous business questions, standardize reporting, and influence priorities. Strong SQL and Python skills are required, along with dashboard development and stakeholder communication. Healthcare data, dbt, Snowflake, and engineering collaboration experience are preferred.

Build analytical frameworks, measurement methodologies, and decision support to drive enterprise decisions across marketing, loyalty, pricing, menu, media, and operations. Mine and integrate customer, transaction, digital, and operational data; develop segmentation, predictive models, and dashboards; lead test-and-learn, incrementality, and forecasting efforts; translate analysis into clear business recommendations and scalable decisioning tools.

Supports strategic pricing initiatives through competitive pricing analysis, market research, pricing data collection and analysis, database and dashboard maintenance, pricing recommendations, price-testing analysis, management reporting, and process improvement. The intern collaborates cross-functionally and helps improve pricing tools, data accuracy, sales performance, profitability, and revenue optimization.

Design and maintain enterprise business intelligence platforms, including dimensional models, semantic layers, data warehouses, Power BI solutions, and Microsoft Fabric integrations. Optimize SQL, DAX, refresh processes, and semantic model performance. Establish BI governance, security, deployment pipelines, source control, testing, monitoring, and documentation. Lead complex initiatives, evaluate emerging technologies, and translate business needs into scalable solutions while communicating technical recommendations and risks to diverse stakeholders.

Serves as the bridge between procurement stakeholders and technical data teams, governing procurement data across ERP, master data, data lake, BI, and reporting platforms. Responsibilities include defining data standards, maintaining metadata and mappings, validating transformations, monitoring data quality, resolving data issues, supporting testing, and enabling analytics. The role also translates business requirements into technical specifications and contributes to procurement transformation and continuous improvement.

Deliver customer-facing technical training in data engineering and AI through virtual and onsite sessions. Create tailored courses, projects, certifications, and assessments aligned with customer roles, tools, and business outcomes. Partner with Customer Success, Sales, Product, and Content teams to design blended learning paths, drive platform adoption, and improve measurable skills. Support diverse technical and non-technical audiences across time zones, with occasional onsite travel and success metrics tied to customer satisfaction, bookings, and professional services revenue.

Leads the architecture, development, and support of enterprise data warehouses, lakehouses, dimensional models, ETL/ELT pipelines, and governed data products using Microsoft Fabric and related tools. Ensures data quality, security, scalability, performance, and reliability for analytics and reporting. Partners with technical and business stakeholders, documents data solutions, guides architecture decisions, mentors team members, and drives continuous improvement of data engineering standards and practices.

Supports enterprise master data applications by gathering and managing business, functional, and technical requirements across MDM, PIM, and DAM platforms. Leads stakeholder elicitation sessions, documents user stories, process flows, wireframes, acceptance criteria, and business rules, and partners with technical teams on solution decisions. Coordinates functional, integration, and user acceptance testing, including defect management, while aligning technical and non-technical stakeholders on priorities and approvals.

The Epic Business Intelligence Developer creates analytics content for Epic data, configures applications, writes SQL reports, and manages data models and analytics catalogs.