Top Hybrid Data & Analytics Jobs

Leads the Journey Intelligence Team’s analytical strategy, manages analysts, develops customer measurement frameworks and segmentation, conducts exploratory and experimental analysis, and translates customer behavior insights into strategic initiatives that improve engagement and the end-to-end customer experience.

Build and maintain production data models supporting supply chain, merchandising, marketing, and CRM decisions. Own data integrity, transformation logic, availability, testing, monitoring, documentation, and efficient data access. Partner with business and engineering teams to translate questions into durable models and self-service tools. Develop Looker dashboards, automate reporting, identify data gaps, define data product requirements, and support tracking improvements.

Designs and develops AWS data pipelines and automated document-processing workflows for structured and unstructured data. Builds chunking, embedding, vector indexing, semantic search, knowledge bases, and RAG integrations. Develops AI agents using Amazon Bedrock and Claude technologies, deploys them through AgentCore, and maintains GitHub Actions CI/CD pipelines. Optimizes systems for scalability, reliability, security, and performance. Requires remote work in western U.S. time zones and travel to client workshops or meetings.

Conduct end-to-end data analysis, translate ambiguous business questions into actionable recommendations, and support decision-making across company functions. Build and maintain dbt models, tests, documentation, curated tables, semantic-layer metric definitions, and BI reporting. Partner with data engineering and stakeholders to ensure data quality, governance, and self-service access for people and AI agents. Maintain dashboards and identify opportunities across multiple business verticals.

Analyzes logistics and fulfillment data to support business decisions and continuous improvement. Develops standardized reporting, dashboards, visualizations, KPI tracking, and scenario analysis across Safety, Quality, Delivery, Cost, and Growth metrics. Uses structured and unstructured data to deliver descriptive, diagnostic, predictive, and prescriptive insights. Trains users on reporting tools, identifies business priorities, and communicates actionable recommendations to leaders. The role is hybrid and requires up to 5% travel.

Support Socrata public data publication, feeds, and integrations; migrate existing publication assets; and maintain accessible public data outputs. The role requires onsite work in Washington, DC on a hybrid basis and may be fulfilled by internal personnel or a teaming partner.

Designs and maintains data pipelines, data lakes, ETL processes, data integration workflows, and enterprise data platforms. Transforms and optimizes data using Databricks, Python, and SQL. Develops dashboards, reports, scorecards, and KPI solutions with Amazon QuickSight and Tableau. Works with PostgreSQL, Oracle, AWS RDS, and Starburst while ensuring data quality, performance, security, governance, and effective data modeling.

Build and operate batch and real-time data pipelines and production data products for an enterprise customer. Integrate databases, APIs, files, and event streams while ensuring data quality, observability, lineage, and reliability. Act as the primary technical customer partner, translating needs into data models, APIs, and delivery plans. Coordinate releases, manage technical projects, resolve production issues, document operations, and provide field feedback to improve the platform.

Designs and maintains complex conceptual, logical, and physical data models supporting finance reporting, analytics, and enterprise data strategy. Partners with business stakeholders, data engineers, governance teams, and technology groups to deliver trusted data products and integrations. Oversees data platform operations, metadata, documentation, performance optimization, data quality, and target-state roadmaps. Supports project and program managers, facilitates meetings, translates business requirements into technical designs, and communicates complex data concepts to diverse audiences.

Designs, builds, and evolves enterprise data lake and supporting AWS platforms across ingestion, storage, processing, integration, and governed consumption. Translates stakeholder needs into scalable architectures, develops reusable ingestion and deployment patterns, implements IAM and entitlement frameworks, and supports audits and control processes. Applies AWS DevOps, infrastructure as code, CI/CD, monitoring, and security practices. Provides technical leadership in Agile delivery, evaluates emerging technologies, and mentors junior developers.