Top Data & Analytics Jobs

Lead the architecture and development of scalable data pipelines and infrastructure. Clean, standardize, and model construction data; build tools for data quality and performance; design integration flows with product, engineering, and customers; apply Python, SQL, and ETL practices; and use AI/ML to improve data classification and mapping. Establish data governance and reliability standards in a high-ownership startup environment.

Analyzes affiliate ecommerce performance, translates data into actionable recommendations, develops dashboards and reporting, identifies growth opportunities, designs tests, and supports editorial, business development, and social teams. The role also maintains analytics processes, automates workflows, and leads ad hoc analysis during major commerce periods.

Own Hazel’s end-to-end data platform, including ingestion, transformation, orchestration, reliability, and warehouse performance. Build low-latency, reliable pipelines and clean data models, ship integrations for e-commerce and advertising sources, and automate integration and transformation work using AI agents. The role requires production ownership of large-scale data infrastructure, strong Python, SQL, and dbt expertise, orchestrator experience, and effective documentation.

Leads commercial data infrastructure, business intelligence, reporting automation, AI-enabled analytics, data governance, and process improvement. Builds dashboards and analytical solutions for forecasting, pricing, profitability, customer segmentation, and market intelligence. Partners cross-functionally with sales, marketing, operations, supply chain, finance, and IT to improve data quality, streamline workflows, and replace manual processes. The role is fully on-site in Louisville, Kentucky, with travel of up to 20%.

Performs complex data analyses, develops reports, dashboards, models, and statistical solutions, and communicates findings to technical and nontechnical audiences. The role produces written summaries and presentations, supports quality improvement, manages multiple projects, represents analytics leadership with clients, and serves as a technology expert and resource for junior staff. Responsibilities include improving analytics efficiency and delivering accurate outputs on schedule.

Manage and develop a team of 4–6 analysts delivering customer reporting and analytics. Lead complex analyses, establish standards for rigor and reproducibility, oversee project delivery, present findings to stakeholders, and partner with Product and Engineering on measurement products and AI-enabled analytics tools. The role requires deep advertising measurement expertise, client-facing communication, dashboard development, and hands-on proficiency in SQL, Python, Excel, statistical methods, and analytics platforms.

Design and operate production-grade data pipelines, backend services, APIs, and agentic AI workflows. Build scalable systems that ingest, transform, and operationalize data for customer-facing and internal applications. Translate ambiguous operational workflows into reliable architectures, improve service observability and performance, and own technical decisions across data modeling, system design, security, and compliance.

Maintains Salesforce data integrity, manages support requests and data loads, builds Salesforce, Tableau, and Power BI reports, analyzes revenue and sales trends, supports migrations and integrations, documents data standards, and provides actionable insights and dashboard training to revenue, executive, sales, marketing, and customer support teams.

Designs and implements scalable physical data models in Snowflake, translating conceptual and logical models into schemas, tables, and views. Collaborates with data engineering, architecture, governance, business, and technical teams on ETL/ELT, data integration, metadata, documentation, compliance, and pipeline optimization. Requires Data Vault 2.0, SQL, Snowflake, governance, and stakeholder management expertise, with pharmaceutical experience preferred.

Supports data gathering, analysis, reporting, dashboard development, process improvement, requirements documentation, solution testing, data cleanup, project tracking, and ad hoc analysis. Collaborates with senior analysts and business stakeholders to provide insights, validate solutions, maintain data integrity, and support business decisions.