Top Senior Data & Analytics Jobs

Own analytics for operational areas by defining KPIs, building Tableau dashboards and SQL queries, validating data quality, uncovering insights, and presenting recommendations to stakeholders and leaders. The role involves requirements gathering, scoping ambiguous analytics initiatives, maintaining dashboards, driving adoption, and proactively identifying opportunities to improve shared-services operations.

Owns enterprise database platforms, applications, APIs, integrations, and data warehouse operations. Leads cloud-based data modernization, Azure platform evaluation, AI-enabling data architecture, governance, security, and Dynamics 365 migration readiness. Translates business requirements into scalable solutions, manages technical project lifecycles, collaborates with vendors and IT leadership, and mentors team members.

Design, build, and maintain data lakes, data warehouses, and end-to-end data pipelines for a multi-tenant SaaS platform. Lead code and design reviews, write infrastructure-as-code, optimize performance and scalability, participate in data governance, mentor junior engineers, evaluate new technologies, automate tests, collaborate cross-functionally, and join on-call rotation to ensure reliable data delivery.

Lead hands-on development and operation of production data pipelines and platforms using PySpark, Python, SQL, and AWS services. Translate requirements into technical designs, data models, SLAs, and reliable pipeline architectures. Establish engineering, data quality, observability, documentation, and coding standards; conduct code reviews; mentor engineers; manage Agile delivery and releases; and use GenAI tools to improve productivity and solution quality.

Design, build, and optimize scalable AWS and Snowflake data pipelines, databases, data models, and cloud-based solutions. Implement ETL/ELT workflows, data quality and monitoring frameworks, CI/CD pipelines, automated recovery, documentation, and performance improvements. Collaborate with stakeholders and cross-functional teams in an Agile environment while conducting advanced analysis using Python and SQL.

Develops market intelligence and analytical solutions using data mining, modeling, forecasting, scenario planning, and visualization. Partners with marketing, sales, supply chain, strategy, finance, and commercial stakeholders to manage data logistics, build data tools, validate outputs, identify market opportunities, and communicate actionable recommendations. Manages multiple projects, presents insights to executive audiences, and supports strategic decision-making.

Owns TrendAI’s AI-generated answer visibility measurement program, including baselines, prompt methodology, recurring reporting, citation and competitive analysis, and entity representation. Translates findings into actionable content, PR, social, and messaging recommendations, partners with cross-functional teams to implement them, and evaluates outcomes. Requires enterprise B2B technology experience, AI visibility expertise, marketing analytics, knowledge-graph familiarity, technical fluency, and people-leadership readiness.

Designs and maintains BI solutions, writes optimized SQL and stored procedures, and builds AI-assisted reports and dashboards using Power BI, Tableau, and Excel. Translates business questions into actionable insights for Sales and cross-functional teams, develops data models, supports reporting migrations, and ensures data quality, governance, documentation, and consistency across platforms.

Lead development of compliance dashboards, automated reports, and integrations between trade compliance systems and ERPs. Translate regulatory data into visuals, manage integration and implementation projects, coordinate cross-functional teams, and serve as subject-matter expert to drive compliance improvements and automation.

Designs and maintains Power BI reports, dashboards, semantic models, and end-to-end analytics solutions. Builds ETL processes, data pipelines, and data transformations, performs advanced SQL/DAX/M work, automates reporting (including approved AI tools), validates data quality, recommends process improvements, and presents insights to technical and non-technical stakeholders. Individual contributor who may lead moderate-risk projects and deliver user training.