Top Hybrid Data & Analytics Jobs

Design and build analytics platforms measuring AI cost governance, ITSM performance, and knowledge-worker productivity. Integrate telemetry (LiteLLM, ServiceNow, collaboration tools) into Snowflake/Fabric, produce executive dashboards, identify AI enablement opportunities, and deliver operational insights and ad-hoc analyses to IT and business leaders.

Lead product and marketing analytics for Morningstar's Individual Investor products by building KPI dashboards, automating reporting, consolidating data sources, and conducting cohort, LTV, and retention analyses. Develop financial forecasting models, evaluate pricing and acquisition impacts, implement tracking with GTM and SQL pipelines, and partner with engineering to maintain centralized data infrastructure and ensure data accuracy to inform growth and product decisions.

Design and build data models, warehouses and lakes; automate ETL pipelines; integrate and troubleshoot diverse data streams (structured and unstructured); analyze logs and complex networks; develop standards, governance, and analytic tools to enable secure data access and downstream consumption.

Lead DEX analytics and tooling to identify and remove employee digital friction using Nexthink and ServiceNow. Build and maintain a Digital Experience Scorecard, produce dashboards and presentations, partner with Enterprise IT and AV teams to standardize meeting-room and collaboration experiences, manage projects to improve tooling, access, and onboarding, and communicate improvements back to employees.

Design and maintain reports, analyses, and dashboards to inform supply chain decisions. Partner with supply chain teams on forecasting, capacity, inventory placement, transportation, and delivery experience. Extract, transform, and load data using SQL and other platforms, ensure data integrity, automate analyses, and respond to senior leader requests. Improve processes and enable self-service reporting.

The Data Scientist III will design online experiments, develop models for causal inference, ensure data quality, and communicate insights across teams.

Design, develop, and maintain end-to-end data pipelines and data products for analytics. Troubleshoot complex data issues, document data sources, onboard backend and 3rd-party data, mentor peers, evaluate and deploy new tools, and collaborate with business partners to enable data-driven decisions.

Lead end-to-end people analytics projects, translate business priorities into measurable analytics strategies, build executive-ready visualizations and measurement frameworks, partner with HR and product teams to operationalize insights, automate analytics workflows, and upskill partners on data literacy and AI-assisted analytics.

Maintain and automate marketing performance reporting, build actionable Power BI dashboards, query and integrate data from ad platforms and CRMs, detect anomalies, and provide insights on CTR, CVR, ROAS, attribution, and testing to support paid media and SEO teams.

Lead end-to-end analytics delivery: define problems, gather requirements, analyze large datasets, build/maintain pipelines, produce insights and dashboards, manage projects and stakeholders, and ensure quality and controls throughout implementation.

Lead Data Engineer responsible for designing, building, and maintaining secure, scalable data pipelines and platforms. Develop data models, implement backup/recovery and archiving strategies, manage access controls, and apply enterprise-authorized AI to accelerate engineering workflows while validating outputs and protecting data sensitivity.

Designs, develops, tests, and maintains scalable, secure data pipelines and architectures. Works across the data lifecycle using Python, advanced SQL, NoSQL, and enterprise AI capabilities. Updates data models, validates AI-assisted outputs, enforces controls and auditability, and applies statistical analysis to support business analytics and product requests.

Designs, builds, deploys and supports enterprise data environments and pipelines across cloud and on-prem systems. Collaborates on infrastructure, monitoring, capacity planning, security, governance, disaster recovery, and integration with enterprise systems. Provides technical leadership for data management, testing, optimization, and operational support to meet SLAs.

Lead design, develop, test, implement, and support cloud-based data solutions and pipelines. Collaborate across Agile teams, mentor engineers, use big data and distributed tools (Spark, Kafka, Hadoop), RDBMS/NoSQL, and cloud data warehouses (Redshift, Snowflake) to deliver performant systems that enable ML and product experiences.

Design, build, and maintain data solutions for Retail Bank. Mine varied data sources, develop BI dashboards and metrics, drive analysis for business insights, and enforce data quality, lineage, and governance working with tech teams and Snowflake/AWS platforms.

Design, develop, test, implement, and support cloud-based data solutions. Collaborate with Agile teams on distributed microservices, streaming and batch data pipelines using big-data tools, data warehouses, NoSQL/RDBMS, and mentor engineers. Perform unit tests and code reviews to ensure performant, production-ready systems.

Lead and scale the People Analytics function by developing global strategy, mentoring the team, partnering with HR and business leaders, and delivering actionable insights. Build reports, dashboards, and prototypes using SQL, Tableau, Workday, and other tools; prioritize rapid iteration, automation, and self-service analytics to influence workforce decisions and drive company-wide change.

Lead and scale the People Analytics function: develop global People Analytics strategy, manage and mentor team members, partner with HR and business leaders, deliver actionable insights via SQL/Tableau/Workday, build self-service analytics, iterate quickly on pilots, and translate complex people data into clear stories that influence company decisions.

Design and maintain predictive dashboards and forecasting models to track pipeline health, win rates, and GTM performance. Build SQL pipelines, conduct statistical and scenario analysis, partner with Sales/Marketing/Finance, and translate insights into actionable recommendations to improve revenue forecasting and operations.