Top Data & Analytics Jobs

Administer and support SQL Server and cloud databases for a tolling environment. Responsibilities include database monitoring, installation, upgrades, patching, migration, performance tuning, troubleshooting deadlocks and blocking, resolving application connectivity issues, supporting high availability, and managing very large databases. The role also provides help desk and application support, uses operating-system scripting, and recommends database improvements while collaborating with engineering and operations teams.

Leads operations intelligence and business solutions for Logistics & Distribution. Translates business needs into reporting, analytics, automation, and AI-enabled tools; develops Tableau and Power BI dashboards, data models, KPI frameworks, and executive insights. Identifies process improvements, evaluates AI use cases, builds Power Platform solutions, supports governance and adoption, and partners with Technology and business teams on scalable solutions, ROI analysis, and digital transformation.

Own production-grade analytics data products, including reusable dbt models, dimensional models, metrics, access controls, tests, documentation, and Lightdash guidance. Partner with stakeholders across GTM, Finance, and data teams to define requirements, reconcile conflicting source data, validate results, and publish trusted metrics. Diagnose data quality issues, collaborate with data engineering, review modeling changes, and establish shared standards. Regularly use and evaluate AI coding agents in analytics workflows.

Build and maintain business intelligence models, dashboards, reports, and compensation analyses for shelter, breeder, and sales channels. Support insurance regulatory reporting, ad hoc analytics, data quality, governance, automation, and performance tuning. Partner with data engineering, compliance, and business teams to improve enterprise data models and enable AI-driven initiatives.

The Data Analyst II supports data extraction, cleansing, validation, transformation, ETL, reporting, dashboard creation, and visualization using SQL, Power BI, and Python. The role also assists with AI-enabled tools, automation, APIs, prototypes, and application workflows. Responsibilities include documenting data processes, validating outputs, communicating insights, supporting data quality and security, collaborating with stakeholders, and leading smaller-scope tasks with guidance from senior team members.

Designs and maintains data warehouse architecture, APIs, ETL pipelines, database objects, and data extracts from sources such as NetSuite, IRI, and point-of-sale systems. Develops Power BI dashboards and supports analysts with reporting. Ensures data quality, security, governance, and performance while researching large datasets and delivering AI-enabled analytics. Collaborates with business stakeholders and manages third-party analytics resources.

Own and maintain the GTM data stack and CRM systems end-to-end: extract and model data, build ETL/Timescale pipelines, manage Salesforce and HubSpot administration and integrations, deliver reporting and forecasting (Power BI/Salesforce), ensure data quality and monitoring, and expose data for AI agents.

Maintain and administer Microsoft SQL Server databases supporting healthcare research administration, compliance, reporting, and operations. Design schemas and tables; develop and optimize stored procedures, queries, scripts, utilities, and reports; manage scheduled jobs; monitor performance, security, backups, recovery, and data integrity; troubleshoot database and application issues; coordinate with web developers; document solutions; and provide technical recommendations to research leaders.

Build Hyperbolic Labs’ data infrastructure from the ground up, owning the data warehouse, ingestion pipelines, data modeling, reliability, governance, monitoring, troubleshooting, and performance tuning. Partner with engineering and analytics teams to support growing products, data sources, BI, and reporting. The role requires deep PostgreSQL expertise, large-scale data experience, and independent ownership of production data systems.

Develops enterprise data architectures, governance frameworks, integration strategies, metadata and master data standards, AI/ML data governance, feature store architectures, data lineage, provenance tracking, synthetic data and cross-domain sharing architectures. Supports governance compliance and creates data architecture roadmaps and modernization strategies for cloud and enterprise environments.