Top Data & Analytics Jobs

Lead analytics for healthcare products by developing end-to-end data models, KPIs, dashboards, funnel and cohort analyses, marketing attribution, and product performance insights. Partner with Product, Marketing, and Member Services to evaluate initiatives, identify trends and risks, and inform strategic decisions. Prepare executive business reviews and communicate data-driven recommendations. Requires advanced SQL, large-dataset analysis, modern analytics environments, AI-enabled workflows, and business intelligence dashboard development.

Lead the design and operation of a scalable data platform, owning ingestion, orchestration, observability, lineage, data modeling, contracts, and ETL/ELT pipelines. Build Databricks and PostgreSQL solutions, implement data-quality controls, anomaly detection, governance, privacy, and compliance practices, and establish reusable engineering standards. Mentor engineers and ensure reliable, traceable data across markets and product lines.

Maintains item master data quality, integrity, and compliance in Oracle Fusion ERP and enterprise repositories. Manages new item requests and attribute changes, enforces governance policies, maintains data dictionaries and SOPs, and monitors workflow SLAs. Performs data profiling, hygiene audits, root-cause analysis, and quality reporting. Collaborates with accounting, quality, technical, and business teams; trains users on submission standards and workflows; and drives continuous process improvement.

Lead enterprise data architecture strategy and roadmap across a global manufacturing organization. Design scalable cloud data platforms, govern data quality and standards, lead Master Data Management initiatives, and enable analytics and AI solutions. Partner with executives, business leaders, engineering, IT, and manufacturing teams to guide enterprise technology decisions and investments using Snowflake, Azure, Oracle, APIs, and streaming technologies.

Own the analytics lifecycle from data ingestion, ETL, modeling, orchestration, validation, and warehousing through BI dashboards and actionable insights. Build SQL/Python analyses and automation, define trusted metrics, quantify customer ROI, improve data quality, and support customer-facing presentations. Prototype machine learning models for product and business problems while designing scalable analytics infrastructure and partnering with Product, Engineering, and CX teams.

Own and evolve Worldly’s production data lake, Postgres warehouse, CDC and streaming pipelines, dbt transformations, orchestration, BI access controls, and graph integrations. Maintain reliable, governed analytics infrastructure using Iceberg, Trino, Dagster, Terraform, and AWS. Support production generative AI workflows involving embeddings, similarity search, extraction, and classification. Responsibilities include data quality, monitoring, security, incident response, disaster recovery, schema governance, and collaboration with data science and analytics stakeholders.

Leads customer data strategy and solution design across loyalty, personalisation, and marketing technology. Oversees a team of three Audience Specialists, develops scalable data capabilities, and works hands-on with SQL, data platforms, segmentation, and audience activation. Partners with Architecture and business stakeholders to deliver initiatives, maintain the customer data roadmap, and support AI-enabled personalisation. Champions data governance, privacy, responsible data use, and commercial outcomes including Voice of Customer and NPS.

Provides database engineering and Oracle DBA support for complex, distributed intelligence systems. Responsibilities include database architecture, design, administration, migration, replication, backup and recovery, performance tuning, security, schema development, scripting, requirements analysis, documentation, and technical issue resolution. Collaborates with engineering, testing, security, management, and customer teams in an Agile environment, supporting high availability, capacity planning, system optimization, and quarterly PI Planning activities.

Lead research on the macroeconomics of AI by authoring flagship reports, building quantitative forecasting models, integrating bottom-up semiconductor and datacenter data into macro estimates, developing LLM-driven research pipelines, performing econometric analysis, and communicating findings to investors, policymakers, and the public.

Analyze and manipulate large datasets supporting energy modeling and SEM programs. Review data before and after modeling, maintain standardized templates and databases, integrate data into statistical software, quality-control models and reports, and create work instructions. The role also involves automating data processing, troubleshooting Visual Basic and Excel tools, managing Smartsheet data, supporting benchmarking reports, and collaborating with internal teams and occasional clients.