Top Hybrid Data & Analytics Jobs

The Business Analytics Lead will deliver business priorities through insights and advanced analytics, manage analytics teams, and integrate advanced analytics into applications.

The Manager, Business Analysis, Reporting leads a team to develop and govern enterprise reporting solutions while ensuring data quality and fostering team growth.

Build and maintain reliable data warehouse models and pipelines to power GTM metrics, dashboards, and automation. Partner with Sales, CS, Product, and Engineering on instrumentation, CRM and usage modeling, data quality, observability, forecasting, and actionable data products for GTM teams.

Lead and manage market research projects from design through debrief: design and organise local and international fieldwork, create questionnaires, analyse quantitative and qualitative data, and produce insightful client presentations and reports.

Build and maintain scalable cloud-native data platforms and pipelines for analytics. Design system architecture, ingest high-volume bounded and unbounded data, optimize performance and cost, write tests and documentation, collaborate with product and EHR specialists, and adopt AI-assisted development tools to improve delivery and quality.

Lead customer integrations by building warehouse-native or managed ClickHouse pipelines, construct semantic metadata layers, canonicalize source data into unified growth models, and act as the technical lead for enterprise deployments while partnering with AI discovery agents to accelerate onboarding and mapping.

Founding lead to define, govern, and deliver canonical investment data products. Hands-on role writing production dbt models in Python/SQL, hardening pipelines, driving adoption of shared data layers, and building a small senior data team while partnering with business, compliance, and vendors.

Build and scale core data infrastructure and foundational datasets. Design, develop, and maintain scalable data pipelines for analytics, ML, experimentation, and product use cases. Implement data quality, audits, alerting, and anomaly detection. Partner with product, engineering, and business stakeholders and help establish long-term, scalable data architecture and tooling.

Design, build, and maintain scalable data ingestion and ETL pipelines across a growing data lake. Define and enforce data quality standards, SLOs, and validation frameworks. Optimize pipelines for performance and cost, expand monitoring and alerting, and enable stakeholders to self-serve on data infrastructure.

Responsible for transforming sales data into strategic narratives, providing insights for executive decision-making, and leading a team of analysts.