Top Data & Analytics Jobs

Design and implement scalable manufacturing data infrastructure by collecting ERP and shop-floor data, building automated Power BI dashboards, standardizing KPIs, validating data, mapping processes, producing regular reports, and recommending automation opportunities to support continuous improvement.

Lead pricing strategy and execution by building dashboards and reports, querying large datasets (e.g., Snowflake/SQL), benchmarking competitors, conducting market research and price-elasticity experiments, and presenting data-driven insights to influence cross-functional stakeholders and drive margin and revenue growth.

Lead workforce analytics and data strategy for Workforce Initiatives by transforming data into actionable insights, building dashboards and predictive models, ensuring data governance and integrations across Workday/ATS/LMS, driving automation and reporting, and partnering with HR, Talent Acquisition, IT, Finance, and operations to inform workforce planning and program effectiveness.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.

Hands-on data-focused software engineer to build, enhance, and maintain Snowflake-based data pipelines, ETL processes, data models, semantic views and governed consumption patterns. Ensure data quality, security, orchestration (Snowflake Tasks/Snowpipe), and partner with stakeholders to deliver business-ready analytics and AI-enabled insights.

Lead Horizon's NY Analytic Insights group to translate analytics into business strategy. Oversee MMM, attribution, dashboarding, AI-assisted measurement, and test & learn initiatives. Partner with BI, advanced analytics, product, and brand teams; drive new business, mentor a 20-person team, and scale analytic solutions across clients.

Lead architecture, provisioning, performance tuning, migration, and security of cloud analytical databases (Redshift, Aurora/Postgres). Optimize high-volume analytical queries for BI tools, manage migrations (DMS/Airflow), automate maintenance with Python/Bash and IaC, and collaborate with data teams to enforce modeling and operational best practices. On-site in DC and requires active Top Secret clearance.

Design, develop, and deploy scalable Power BI dashboards and semantic models; build and optimize ETL/data pipelines with SQL and Python; architect cloud data solutions (Snowflake/Azure/Databricks); integrate APIs and AI/ML insights (predictive, NLQ, generative AI); lead data governance, quality assessments, and enable self-service analytics.

Partner with product, marketing, and biz-dev to drive data-driven growth. Design, run, and analyze A/B tests; use ML and analytics to inform acquisition and partnership strategies; automate processes to improve operational efficiency.

Own analytics for a core business area (growth, product, AI, or partnerships): define problems, build metrics/reports, run analyses and experiments, surface insights, and drive cross-functional decisions to improve key business metrics end-to-end.

Own the analytics function for an embedded business unit: define problems, build reports and experiments, analyze data, surface insights, and drive cross-functional decisions to improve product, growth, AI, or partnerships.

Own and evolve end-to-end data pipeline architecture across ingestion, transformation, modeling, and serving. Lead platform improvements (cost, compute efficiency, access control), CI/CD, monitoring, and incident response. Drive cross-team technical initiatives, mentor engineers, and integrate AI tooling to improve workflows while remaining hands-on building and debugging production pipelines.

Lead combined Analytics Engineering and Data Engineering teams owning the end-to-end data roadmap from ingestion to trusted metrics. Manage hiring and performance, set architecture and platform investments, enforce testing/monitoring/documentation standards, review technical decisions, and partner with product and business stakeholders to translate needs into prioritized deliverables.

Lead and grow a Data Engineering & Analytics team to deliver governed, reliable data products. Own data pipelines, dbt models, BigQuery, Airflow, and Python-based tooling; manage intake/prioritization (Jira); advance analytics from reporting to predictive/prescriptive models; ensure PHI-safe practices, stakeholder alignment, and on-time delivery of reports, invoices, and analytics.