Top Data & Analytics Jobs

Build and optimize scalable Databricks data pipelines across a medallion architecture. Develop data models, implement data quality checks and validation, integrate Azure services, and ensure data accuracy, governance, lineage, security, and performance. The role requires designing config-driven pipelines supporting CDC and event-based processing, maintaining CI/CD deployments, and working with structured and unstructured data across SQL and NoSQL systems.

Supports business planning through data and business analysis, forecasting, financial modeling, performance measurement, market research, and industry trend analysis. Collaborates with cross-functional teams on data collection and supports priority projects. The role requires analytical thinking, data manipulation, statistical analysis, financial modeling, Excel and Access proficiency, communication skills, and basic project management knowledge.

Lead the architecture and delivery of modern data and analytics platforms for clients. Design governed, secure solutions using Microsoft Fabric, Azure, Databricks, Power BI, and Purview. Translate business needs into scalable architectures, estimates, roadmaps, and delivery plans. Guide architecture reviews, governance, CI/CD, testing, monitoring, and operational readiness while enabling AI, Copilot, RAG, and intelligent application initiatives. Serve as the technical lead and trusted advisor for client engagements.

Design, build, and operate large-scale data platforms and production ETL/ELT pipelines. Partner with data science, analytics, and business teams; manage cross-functional delivery, QA, observability, data quality, experimentation infrastructure, and statistical model validation. Deploy containerized workloads through Docker, Kubernetes, CI/CD, and Helm. Own data operations, monitoring, incident response, SLAs, runbooks, and pipeline reliability while delivering accurate, scalable, and cost-efficient data assets.

Analyzes transaction and business data using SQL, builds and maintains BI dashboards, handles ad hoc requests, and translates stakeholder needs into actionable insights. Partners with Finance and Operations, documents analytical best practices, mentors junior team members, promotes data literacy, and designs A/B tests to guide feature prioritization.

Supports research and analytics on economic, real estate, and financial trends. Responsibilities include organizing and evaluating data, developing quantitative and qualitative insights, maintaining internal databases, preparing market analyses, and creating content for presentations, webinars, podcasts, websites, and other communications.

Leads business analysis, advanced analytics, KPI development, data modeling, reporting automation, and AI/ML initiatives supporting global data-center construction and operational excellence. Builds datasets, dashboards, performance metrics, forecasts, and scenario models; translates complex findings for executives; aligns technology solutions with business needs; and promotes data governance, documentation, process improvement, and analytics maturity across cross-functional teams.

Develop and support a multi-terabyte inventory and position data platform for financial markets. Responsibilities include migrating KDB+ data to Snowflake, database engineering, data modeling, access controls, performance optimization, testing, platform upgrades, cloud-based data distribution, and stakeholder collaboration. The role also maintains existing KDB+ systems while contributing to a greenfield Snowflake architecture in an Agile environment.

Designs and maintains scalable data pipelines, ETL/ELT processes, metadata repositories, catalogs, and governance solutions. Integrates structured and unstructured data across cloud platforms, develops data warehouses, lakes, and lakehouses, and implements lineage, quality monitoring, automation, and compliance controls. Collaborates with architects, analysts, data scientists, governance teams, and business stakeholders to support analytics, AI/ML, business intelligence, data discovery, and self-service reporting.

Analyze underwriting and claims data to set rates, prepare statistical analyses and filings, project loss trends, support product development, and present findings to stakeholders to inform pricing strategy.