Top Data & Analytics Jobs

Build and own end-to-end compliance data pipelines and models (case, alert, entity, transaction, risk features). Ensure data quality, monitoring, lineage, and audit-ready documentation. Partner with Compliance and engineering to close upstream gaps, improve detection signal quality, and implement measurement frameworks and reporting for control effectiveness.

Lead Data Engineer responsible for designing, developing, testing, implementing, and supporting cloud-based data solutions. Collaborate across Agile teams to build distributed, real-time data and streaming systems, mentor engineers, perform unit tests and code reviews, and leverage big data, NoSQL, and cloud data warehousing technologies.

Lead Data Engineer designs, develops, tests, and supports cloud-based data solutions. Collaborates with Agile teams, mentors engineers, works with machine learning and distributed systems, implements data warehousing and streaming pipelines, and ensures code quality and performance.

Lead Data Engineer responsible for designing, developing, testing, implementing, and supporting cloud-based data solutions. Collaborate across Agile teams on distributed microservices, streaming, and machine learning pipelines using Java/Scala/Python, RDBMS/NoSQL, and data warehousing (Redshift/Snowflake). Mentor engineers, perform unit tests, and deliver performant production systems.

Design, build, and operate enterprise data pipelines and Lakehouse data products on Azure. Lead migrations, implement medallion architectures, optimize Spark and distributed SQL workloads, enforce CI/CD and observability, and support production incident response while partnering with architects, data scientists, and stakeholders.

Lead design and build of enterprise-scale, AI-enabled data platforms and pipelines on Azure and Snowflake. Define architecture, standards, CI/CD, data quality, and production ownership. Enable AI/ML data pipelines, mentor engineers, and collaborate with architects, data science, and product teams to ensure scalable, secure, and cost-effective solutions.

Design, build, and optimize cloud-native enterprise data platforms and ETL/ELT pipelines on Snowflake and Azure. Lead migrations, performance tuning, reliability, cost optimization, and support analytics/AI workloads. Act as technical SME, mentor junior engineers, and improve platform observability and operational maturity.

Lead a team to operate and scale CarGurus' data platform across ingestion, orchestration, storage, and observability. Own roadmap, SLAs, cost, security, and quality controls; improve developer experience; collaborate with product and stakeholders to prioritize initiatives, resolve incidents, and drive platform reliability and scalability.

The Senior Pricing and Packaging Analyst will analyze data to inform pricing strategies, develop recommendations, and work collaboratively across teams to implement these strategies.

The Senior Customer Lifecycle Analyst leads data-driven projects focusing on customer retention, engagement, and lifetime value, leveraging advanced analytics and visualization tools to provide business insights and recommendations.

Lead automation and measurement of the AI Governance program by building self-service dashboards, tracking Time-to-Approval and throughput, analyzing trends to remove bottlenecks, producing C-suite Evidence Packs, recommending workflow improvements, and collaborating with delivery analysts to increase governance maturity and operational throughput.

Analyze transactional and operational payments data to monitor performance, detect risk and fraud, and improve collections. Build, validate, and automate daily/weekly/monthly reports and alerts, consolidate data sources, deliver insights to stakeholders, and support special analytics projects to drive operational efficiency.

Designs, builds, and supports scalable data services and infrastructure across multiple platforms. Collaborates with users, developers, operations, and business partners to define requirements, perform data migration and transformation, ensure data accuracy/security, and maintain availability and scalability. On-call rotation and in-office presence required.

Design, build, and maintain optimized, highly available data pipelines and the BMG Data Warehouse. Lead medium-to-complex data integration, data modeling, code reviews, QA, and cloud migration efforts. Collaborate with business partners to translate requirements into solutions, resolve technical issues, and support analytics and reporting needs while adhering to policies and compliance.

Lead analytics consultant responsible for designing and delivering enterprise-wide fraud monitoring analytics, dashboards, KRIs/KPIs, and automated reporting. Perform complex exploratory and root-cause analysis on large structured and unstructured datasets, develop predictive and anomaly detection models (including graph/network analysis), produce executive presentations, advise senior stakeholders, support remediation and regulatory deliverables, and lead/mentor analytics projects and junior analysts.

Design, build, and maintain optimized, highly available data pipelines and the BMG data warehouse. Lead medium-to-complex data engineering initiatives, perform solution design, code reviews, QA, data integration, and collaborate across teams. Support cloud migration and ensure compliance with data policies for reporting and analytics.

Deliver data engineering and ETL solutions to support client analytics. Build and maintain data pipelines, optimize SQL, design data architecture (star/snowflake models), create BI reports/dashboards, improve data quality, and support client engagements in regulated environments while learning and growing technical and client-facing skills.

Lead data engineering engagements to design, build, and maintain ETL/ELT pipelines and cloud data architectures. Manage client accounts and mentor teams, leverage tools like DataStage, AWS/Redshift, DB2/SQL Server, GoldenGate, and BI/visualization platforms to deliver analytics, performance tuning, and scalable reporting solutions.

Lead a multi-disciplinary analytics team to deliver dashboards, data pipelines, AI/ML models, and decision-support tools for embedded controls. Own people leadership, end-to-end analytics product delivery, MLOps and data engineering strategy, stakeholder engagement, and change leadership to drive data-first practices across GM.

Design, build, and maintain Python data pipelines and business data objects. Implement source-to-target mappings, CI/CD pipelines, unit and integration tests, and deploy solutions. Apply software design and architecture best practices, mentor team members, and resolve complex technical problems across functional teams.