Top Data & Analytics Jobs

Leads a team of data analysts supporting Marketing, Digital, Customer, and DEI functions. Oversees dashboards, reporting, advanced analytics integration, data requirements, quality assessment, visualization, and business insights. Partners with Data Science, Data Engineering, Technology, business units, and vendors to translate requirements into actionable solutions and drive analytics adoption. Coaches analysts, manages priorities, and supports strategic use cases using SQL, Python, cloud data platforms, experimentation, and business intelligence tools.

Analyze contributor performance, dataset quality, production efficiency, and client delivery metrics. Build dashboards and reports, conduct cohort and trend analysis, monitor quality benchmarks, identify data integrity issues, and translate findings into actionable recommendations. Collaborate with Data Operations, Engineering, Product, and Quality Assurance teams to define metrics and evaluate improvements.

Lead BI developer owning end-to-end reporting for marketing verticals. Build and standardize dashboards, model complex/third-party data (LookML), partner with Yield, Paid Media, and Account Management to deliver actionable analyses that optimize campaign performance, conversion, and revenue.

Build and maintain production ETL/ELT pipelines, data models, and curated datasets for analytics and AI applications. Ingest data from databases, APIs, SaaS tools, and event streams; implement quality checks, monitoring, documentation, governance, and access controls. Collaborate with analysts, data scientists, and ML engineers on reporting, feature datasets, AI search, and RAG applications. Optimize query performance and pipeline costs while using Git, code reviews, and CI/CD for safe releases.

Build and maintain data pipelines, integrations, models, warehouses, and cloud data infrastructure. Support data quality, governance, security, monitoring, incident response, documentation, and downstream analytics. Use Python, SQL, Databricks, Azure, dbt, and related tooling in a code-first, agile environment. Collaborate with analytics engineers and stakeholders while developing data engineering skills under mentorship. Participate in planned maintenance and occasional after-hours support for critical data operations.

Build and maintain scalable data infrastructure, pipelines, workflows, and large-scale data processing systems. Develop Python- and SQL-based solutions, integrate data from multiple sources, support machine learning model deployment and MLOps, monitor pipeline health, troubleshoot issues, and ensure data quality. Collaborate with data scientists, analysts, and stakeholders while documenting processes and applying data governance and security best practices.

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.

Owns the program reporting and analytics function, including dashboard architecture, reporting migration, data governance, data integrity, trend analysis, forecasting, and executive decision support. Leads reporting analysts and document control staff, maintains deliverable reporting accuracy, establishes metrics and quality standards, and ensures audit-ready traceability. Requires advanced Power BI, Excel, and reporting leadership experience in a program environment.

Supports end-to-end market research projects, including questionnaire and discussion guide development, data collection, quality control, analysis, visualization, reporting, and client-ready deliverables. Collaborates with internal teams and subcontractors while developing expertise in quantitative and qualitative research methodologies, software, and technology platforms. The role requires strong communication, analytical thinking, organization, attention to detail, and eagerness to learn.

Designs and maintains scalable enterprise data architectures and ETL/ELT pipelines on Microsoft Fabric and Azure. Responsibilities include developing Python-based data solutions, optimizing Fabric warehouses and lakehouses, implementing governance, security, lineage, monitoring, and CI/CD, and integrating diverse data sources. The role partners with data science, machine learning, business intelligence, engineering, and business teams to support analytics and model training while improving platform reliability, scalability, and cost efficiency.