Top Senior Data & Analytics Jobs

Develop and maintain scalable dbt models, dimensional data models, semantic layers, metrics, documentation, tests, and data governance on Snowflake and modern data platforms. Partner with cross-functional stakeholders to define KPIs and deliver trusted self-service analytics. Investigate data quality issues, optimize workloads, improve platform reliability, mentor junior team members, and explore AI-driven workflow automation.

The Senior Data Analyst serves as a bridge between business stakeholders and enterprise data platforms. Responsibilities include defining KPIs, analyzing customer and commercial data, building dashboards and reporting solutions, developing SQL and Python data transformations, managing pipelines, integrating enterprise systems, and establishing data governance and quality standards.

Build and maintain scalable data pipelines, analytics data warehouses, ETL processes, data models, and infrastructure supporting reporting, analytics, and machine learning. Ensure data quality from creation through presentation layers, translate stakeholder needs into deliverables, improve tooling and pipeline reliability, and participate in on-call support. The role involves modern big data architecture, containerization, cloud platforms, and data engineering technologies.

Designs and maintains Snowflake data models and ingestion pipelines supporting enterprise reporting across retail, cultivation, manufacturing, marketing, and finance. Refactors Power BI logic into governed, tested, version-controlled warehouse models; establishes modeling standards, data quality monitoring, documentation, and lineage. Partners with analysts and stakeholders to develop reusable reporting solutions, supports semantic and BI tooling, evaluates data platform technologies, mentors analysts, and contributes to shared pipeline ownership.

Leads multidisciplinary data engineering and research projects supporting sleep physiology and wearable-device modeling. Designs and maintains multimodal data pipelines, ETL workflows, schemas, databases, cloud infrastructure, and machine-learning data products. Oversees data ingestion, cleaning, performance optimization, governance, documentation, and regulatory support while mentoring engineers and analysts. Translates scientific hypotheses into scalable engineering solutions, communicates progress to leadership, and provides technical oversight across the full data ecosystem.

Builds and maintains scalable data pipelines, ETL infrastructure, data warehouses, and analytics tools. The role assembles complex datasets, automates processes, optimizes data delivery architecture, and supports cross-functional data initiatives. Collaborates with executive, product, data, and design stakeholders to resolve technical issues and improve analytics systems. Requires proficiency in SAS, Python, Java, MATLAB, SQL, NoSQL, Hadoop, MapReduce, Hive, Presto, UNIX, and Linux, with JavaScript, R, and basic machine learning preferred.

Lead design and governance of the company's sustainability data ecosystem. Build automated SQL/Python data pipelines, curate datasets and Power BI outputs, ensure methodology-aligned GHG and water accounting, support disclosures and third-party assurance, and deliver customized data packages for customers and investors.

Leads enterprise business intelligence development, translating stakeholder goals into scalable dashboards, reports, KPIs, and analytics. Partners with data engineering, mentors developers, leads medium-sized projects, supports QA and production applications, researches system issues, and contributes to BI architecture, roadmap planning, user education, and stakeholder prioritization. The role includes rotational after-hours on-call support and minimal travel.

Build scalable analytics solutions for the Public Sector business, including dashboards, data models, tables, metric definitions, and ad hoc analyses. Own data quality, partner with Operations and Finance on efficiency and cost analysis, and translate complex findings into actionable insights. Drive cross-functional projects from ambiguity to completion while supporting planning, pricing, and business decision-making.

Leads enterprise data stewardship standards by maintaining glossaries, canonical definitions, business rules, RACI accountability, and decision records. Facilitates cross-functional forums to resolve terminology and governance conflicts, partners with Data Governance and business process owners, and ensures standards are reflected in planning systems, analytics, data products, and AI initiatives. Tracks adoption and supports stewardship operating-model maturity within a matrixed biotechnology organization.