Top Data & Analytics Jobs

Summer Data Engineering internship supporting the data engineering team. Candidates should be rising juniors or seniors studying Computer Science, BIS, MIS, or a related field, with basic Microsoft Word and Excel skills, 40 WPM typing speed, strong communication and organizational abilities, and the capacity to multitask.

Build CodeRabbit’s foundational BI capabilities, executive and board-level dashboards, governed dbt data models, and self-serve analytics workflows. Analyze finance and go-to-market performance, including ARR, pipeline, margins, forecasting, and billing. Partner with Finance, GTM, and leadership to establish trusted metrics, improve data infrastructure, and develop agentic tools that generate reviewed dashboards and insights.

Owns the enterprise Power BI ecosystem, including data modeling, ETL/ELT pipelines, dashboards, reporting, administration, governance, security, and support. Leads BI implementations, platform maintenance, testing, documentation, process improvements, stakeholder training, and adoption of Microsoft Fabric, Databricks, and AI-enabled analytics. Requires strong Power BI and Azure Data Factory expertise, business requirements translation, analytical problem-solving, communication, and potential people leadership. Travel up to 20% domestically and internationally is required.

Data Engineering Intern supporting MEMX exchange data projects. Responsibilities include collecting, organizing, validating, and improving data processes used for reporting and analysis. The intern will collaborate with technology teams, communicate technical findings, and gain hands-on experience with financial-market data while working hybrid from the Midtown Manhattan office during summer 2027.

Supports gas compressor engineering and operations through portfolio data governance, financial and resource analysis, forecasting, dashboards, reporting, and decision support. Maintains Planview data, develops Power BI and related analytical tools, improves processes through automation and AI-enabled solutions, and communicates actionable insights to engineering, finance, operations, and leadership stakeholders.

The Senior Applications Analyst oversees Business Needs Assessments for Oracle Cloud ERP, optimizing applications and translating business requirements into system designs. Responsibilities include leading documentation, managing the application lifecycle, and collaborating with technical teams to ensure functionality and data integrity.

The Senior Analytics Engineer builds and maintains data models, ETL pipelines, analytics products, business intelligence solutions, and visualizations. The role partners with stakeholders, Data Governance, Data Science, and Data Platform teams to define metrics, improve data quality, support AI and machine learning initiatives, and establish software engineering practices. Additional responsibilities include DataOps, workflow orchestration, technical documentation, business advising, and emergency response support. The position requires advanced SQL and Python skills, data engineering experience, and travel up to 10%.

Develop enterprise BI dashboards, reports, semantic models, and analytical solutions using Power BI, SQL, and Azure platforms. Translate business requirements into governed data models, implement DAX and Power Query solutions, optimize performance, and support data quality, lineage, security, audit, and regulatory reporting. Collaborate with Claims, Underwriting, Finance, Operations, Data Engineering, and executive stakeholders while integrating insurance and third-party data sources.

Develop and maintain data pipelines, infrastructure, and integrations supporting analytics, data science, and business intelligence. Ensure data quality and integrity, optimize workflows, and collaborate with Operations, IT, Accounting, HR, Property Services, Marketing, and other departments. The role requires SQL Server, programming, shell scripting, cloud, containerization, version control, and data pipeline knowledge, with occasional travel and flexible scheduling as project deadlines require.

Leads analytics initiatives, data modeling, executive dashboard development, KPI reporting, forecasting, predictive modeling, experimentation, and AI-assisted analytics. Partners with Marketing, Content, Product, Engineering, and leadership to translate complex data into strategic recommendations. Owns Sigma reporting, data definitions, downstream dbt models, and data quality efforts while mentoring junior analysts.