Top Data & Analytics Jobs

Own and optimize data infrastructure and ETL/ELT pipelines using SSIS and Microsoft Fabric. Build and maintain SQL Server data warehouse staging, transformations, and lakehouse ingestion. Implement CI/CD, version control with GitHub, monitor pipeline health, troubleshoot data issues, document data flows, and translate stakeholder requirements into data engineering solutions that support BI reporting.

Develop and execute pricing models and analyses to optimize trailer sales profitability across assigned stores and markets. Use large datasets and competitor surveys to recommend pricing, support field initiatives, monitor pricing adherence, and communicate insights to leadership and stores.

Own and harden Plot's core data platform: stabilize high-throughput ingestion, design read-optimized schemas and partitioning, separate transactional vs analytical workloads, ensure performant data access for dashboards and AI agents, write RFCs, and raise reliability and observability across teams.

Design and implement scalable data ingestion, ETL/ELT pipelines and transformations into Microsoft Fabric using ADF and notebooks (Python/Pandas/Spark). Build and maintain dimensional data warehouse models, ensure data quality, performance tuning, and prepare data for semantic models. Collaborate with stakeholders, participate in code reviews, documentation, and operational handoffs while establishing standards for deployment and governance.

Lead the design and execution of migrating legacy databases to Databricks, focusing on architecture, performance optimization, pipeline engineering, and governance. Collaborate with teams to ensure best practices and knowledge transfer in data platform development.

The Product Analyst will design experiments, analyze user behavior, and communicate insights to drive engagement and retention decisions effectively.

Design, develop, and manage enterprise BI solutions including ETL, data models, reports, and dashboards. Optimize performance, perform data quality audits, lead requirements gathering, mentor junior staff, and support BI infrastructure upgrades and troubleshooting.

Analyze large datasets to produce actionable insights and recommendations; build and maintain BI dashboards and KPIs; partner with stakeholders to inform decisions; champion data quality and collaborate with Data Engineering and Data Science to improve data foundations.

Design and own end-to-end data domains and pipelines for plant sensors, lab results, and historians. Build schemas, ensure data quality, observability, and lineage, and supply model-ready time-series and analytical datasets to ML and operations teams. Mentor junior engineers and define data contracts.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.