Top Hybrid Data & Analytics Jobs

Analyze data to drive business strategy, create reports and dashboards, ensure data quality, and collaborate across departments for insights.

Design, build, and maintain high-quality data models and a governed semantic/metrics layer (Snowflake semantic views) to enable self-service analytics. Partner with analysts and business stakeholders to define metrics, produce certified BI content (Tableau, Redash), ensure data quality and privacy, optimize model performance, and mentor junior team members.

Lead strategic insights and ad measurement projects, analyze complex datasets, craft narratives connecting brand lift to business outcomes, partner with clients and cross-functional teams, and drive process improvements and customer-facing recommendations.

The Data Engineer III will develop data pipelines, integrate enterprise data, and optimize data processes in a cloud environment, working closely with various teams.

Own and operate the iMData platform: design and build Databricks-based ETL pipelines using PySpark and medallion architecture, create gold-layer star schemas, migrate assets from Synapse to Databricks, implement CI/CD and Terraform IaC, ensure data security and observability, mentor junior engineers, and collaborate with stakeholders and ML engineers to deliver production-grade analytics and AI-ready data.

Lead analytics for Udemy Japan partnerships: build and maintain KPIs and dashboards, perform in-depth business and partner analyses, support forecasting and partner-facing events, and provide data-driven insights to sales, leadership, and global partner operations to drive regional revenue growth.

Entry-level Data Engineer responsible for building and maintaining cloud-based data assets and pipelines, improving data quality and automation, investigating data integrity issues, and collaborating with architects, analysts, and stakeholders. Uses SQL and Python, participates in Agile practices, leverages AI-powered developer tools for spec-driven development, and follows responsible AI and data privacy practices.

Lead the implementation of evaluation frameworks for AI systems and clinical assessments, translate clinical evaluations into rubrics, and supervise a team of analysts and engineers.

As a Data Analytics Engineer, you'll build and manage data models in Snowflake, structure datasets for optimal AI performance, and own data transformation while ensuring quality and accessibility for all teams.

The Senior Analytics Engineer transforms curated data into analytical assets, develops BI-ready models, and collaborates with data stakeholders to deliver analytics solutions.