Top Data & Analytics Jobs

Own Eve’s data platform end to end, including ingestion, orchestration, incremental dbt models, Snowflake administration, Terraform infrastructure, observability, access controls, and pipeline reliability. Build schema-change detection, freshness SLAs, CI environments, and incident processes while managing performance and compute costs. Partner with analytics engineers and stakeholders to maintain trusted data for reporting and AI systems, using AI-assisted development and documenting platform standards.

Manages programmatic analytics and insights for client accounts, leading measurement frameworks, brand lift studies, incrementality testing, and A/B experiments. Develops media and campaign strategies, communicates performance insights to clients, and supports pitches and QBRs. Oversees, mentors, and develops analysts while partnering with Product, Engineering, Sales, and Customer Success teams to improve measurement tools, campaign optimization, and analytical capabilities.

Analyze post-sales customer lifecycle data, including adoption, retention, renewals, churn, and expansion. Build Salesforce reports and dashboards, query and validate data with SQL, and create recurring analyses and visualizations using Excel, Tableau, and other BI tools. Partner with Customer Success, CS Operations, Analytics, BI, and Sales Systems teams to improve reporting, investigate trends, identify risks, and communicate actionable insights to technical and non-technical stakeholders.

Designs conceptual, logical, and physical data models for R&D research and clinical domains. Translates scientific and business requirements into reusable, scalable, AI-ready data structures that support analytics, machine learning, data integration, and standardized workflows. Partners with domain experts, data engineers, architects, data scientists, and governance teams to apply enterprise standards, schemas, ontologies, metadata, quality rules, and lineage. Promotes shared data assets and ensures models are implementable, interoperable, and aligned with evolving R&D needs.

Leads revenue growth analytics across pricing, promotions, assortment, and market trends. Develops pricing models, promotional strategies, forecasts, KPIs, dashboards, and predictive analyses to improve sales and profitability. Partners with Sales, Marketing, Finance, and Category Management to provide actionable recommendations, influence strategic decisions, and support planning across retail, commercial, eCommerce, and direct-to-consumer channels.

Build and optimize scalable batch and streaming data pipelines using Python, PySpark, SQL, and Apache Spark on AWS. Develop EMR data processing jobs, lead an Apache Airflow orchestration proof of concept, integrate Amazon Q for data quality and documentation, and implement GitLab CI/CD with infrastructure-as-code. The role emphasizes data governance, security, automation, performance, scalability, and cost efficiency while collaborating in Agile teams and presenting proof-of-concept findings.

Leads a team of data analysts while delivering business intelligence insights across Marketing, Product, Operations, and Finance. Owns the Tableau environment, including governance, permissions, licensing, data quality, and platform capabilities. Develops dashboards, KPI frameworks, and analytics roadmaps; oversees marketing attribution and campaign measurement; partners with Data Engineering on data availability; and drives stakeholder adoption of analytics products.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.

Lead design and implementation of scalable Databricks Lakehouse solutions using Delta Lake, Unity Catalog, and MLflow. Advise stakeholders, drive cloud data platform modernization across Azure/AWS/GCP, ensure data governance and quality, optimize performance and cost, and mentor teams. Support presales, deliver billable consulting, and champion AI/ML-enabled data solutions to translate platform capabilities into business outcomes.

Build and operate data platform services, APIs, SDKs, schemas, validation tools, event-driven pipelines, and reverse ETL workflows. Improve Kafka-based data delivery, schema evolution, observability, lineage, access controls, privacy, and compliance. Partner with engineering, analytics, data science, security, and infrastructure teams to create reliable, self-service data workflows. Operate AWS services, infrastructure as code, monitoring, alerting, and incident response.