Top Data & Analytics Jobs

Supports private-market document processing, data-quality reconciliation, exception triage, workflow management, and offshore team coordination. Serves as a subject-matter expert on private-market data, analyzes trends, documents operational logic, identifies process improvements, and collaborates with Product, Data, and Engineering teams on roadmap and systemic fixes. Provides operational summaries and data-quality reports to support client-facing teams.

Build, deploy, monitor, and support data pipelines for connected devices, web applications, and mobile applications. Collaborate with internal customers, AWS Cloud Architects, and agile teams to develop scalable serverless data solutions using Python, SQL, Snowflake, Databricks, and AWS technologies. The role includes full lifecycle pipeline management, production support, technology evaluation, and participation in data product development under the supervision of a Senior Data Engineer.

Analyze revenue performance, forecasting, business drivers, and market trends to support planning and commercial growth decisions. Partner with Sales, Finance, Business Intelligence, and other stakeholders to identify risks, opportunities, and actionable insights. Develop segmentation, opportunity-sizing, prioritization analyses, and investment business cases. Improve recurring reporting and planning processes through automation and scalable tools, translating complex data into clear recommendations for senior leadership.

Build and maintain recruiting data pipelines, datasets, integrations, dashboards, automations, and data quality controls. Partner with recruiting, data, security, privacy, engineering, and business teams to improve operational reporting and workflows. Responsibilities include integrating ATS and HR systems, monitoring pipeline stability, supporting writeback processes, designing secure access solutions, documenting sensitive workflows, and adapting data products as recruiting processes evolve.

Own Tomo’s data function, strategy, roadmap, platform health, and cross-functional measurement. Build and lead teams spanning data science, analytics, business intelligence, and data engineering. Design experiments, marketing attribution models, SQL queries, and dbt models while maintaining reliable data infrastructure. Partner with Product, Engineering, and executives to improve instrumentation, translate business questions into insights, and establish scalable data processes.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead analytics and reporting for alternative credit portfolios: monitor and analyze investment, portfolio and fund performance; produce monthly/quarterly/ad hoc client reports; maintain data integrity and reporting processes; support investor due diligence and custom requests; coordinate with valuation, fund accounting, investor relations, compliance and portfolio managers.

Senior individual contributor leading end-to-end business and systems analysis for complex finance and compensation systems. Drive requirements, assess system impacts, investigate data discrepancies, and recommend scalable solutions. Partner cross-functionally with Finance, IT, Product, and Operations. Mentor analysts, present findings to senior leaders, and ensure systems align with financial controls and operational requirements.

Leads data engineering and analytics engineering teams delivering production pipelines, curated data products, semantic models, dashboards, and governed Databricks lakehouse capabilities. Owns platform administration, data quality, observability, security, cost optimization, reliability, and engineering standards. Manages internal and external resources, mentors engineers, drives AI-assisted development, partners with stakeholders, and reports roadmap progress to leadership. Requires strong hands-on Databricks expertise, technical leadership, advanced SQL, data modeling, CI/CD, and up to 5% travel.

Own marketing funnel analytics from end to end by monitoring metrics, diagnosing performance drivers with SQL and Python, building Snowflake/dbt models, and maintaining Periscope dashboards. Translate findings into actionable recommendations for leadership, partner with Marketing, Risk, and Engineering on strategy and release impact analysis, and use AI tools while validating their output. Support team development through knowledge sharing, code review, and mentoring junior analysts.