Top Data & Analytics Jobs

Develops Power BI dashboards, leads data migration to a new fundraising and ERP system, validates and reconciles data, gathers reporting requirements, builds Power Automate workflows, documents processes, supports staff, and coordinates third-party data integrations. The role requires strong analytics, business intelligence, SQL, data modeling, reporting, and stakeholder communication skills, with approximately five years of experience.

Build and maintain scalable dbt data models, transforming raw data into trusted, documented datasets. Own warehouse data modeling and metric definitions, establish testing and code review standards, monitor data quality, optimize query performance, and troubleshoot reporting discrepancies. Partner with engineers, analysts, and business stakeholders to translate business needs into reliable pipelines. Mentor junior engineers and contribute to technical best practices and tooling decisions.

Lead and develop an analytics engineering team, define the analytics roadmap, and establish scalable standards for data modeling, business intelligence, and AI-enabled analytics. Partner with leadership, Operations, Engineering, and Product to solve complex business problems, deliver actionable insights, optimize data pipelines, and build a trusted data foundation. Champion documentation, data literacy, and evidence-based decision-making across the organization.

Lead and grow Confido’s data engineering team, initially managing an analytics engineer while remaining hands-on with SQL, data models, pipelines, and code reviews. Own warehouse architecture, orchestration, tooling, data standards, monitoring, and metric definitions. Hire and develop engineers, prioritize the team’s roadmap, collaborate across departments, and improve data reliability, documentation, and reporting across the company.

Owns fraud and market-abuse detection models, rules, and partner-facing surveillance reporting across trading data. Investigates wash trading, collusion, hedging, reverse trading, and other suspicious activity; calibrates thresholds, validates false positives, maintains data quality, and produces evidence-based findings. Requires strong SQL, cloud data warehouse experience, futures and derivatives knowledge, anomaly detection expertise, and the ability to communicate findings to partners and executives.

Design and govern enterprise data architectures that make customer data secure, trustworthy, and AI-ready. Lead data modeling, ETL/ELT, integrations across cloud, ERP, CRM, and legacy systems, vector and retrieval data foundations, data quality, lineage, and compliance. Develop reusable architecture frameworks, evaluate tooling, mentor engineers, advise senior customers, and provide platform feedback. Support multiple concurrent forward-deployed customer engagements involving agentic AI, RAG, and LLM/SLM workflows.

Analyze Experian portfolio repayment performance, credit risk, underwriting and credit-limit changes, collections, funnel metrics, cohort LTV, and unit economics. Own partner analytics models, data definitions, reporting, alerting, and data quality monitoring. Collaborate with Product, Engineering, Partnerships, Finance, and Experian to guide roadmaps, evaluate experiments, identify risks, and support business reviews.

Analyze marketplace and product performance using SQL, support experiments and advertising-effectiveness studies, build reusable datasets, QA metrics, and document analytics. Collaborate with analytics engineers, data scientists, product managers, engineers, and commercial teams while developing skills in statistics, causal inference, Python/R, and marketing science.

Build and lead Apptronik’s People Analytics function, developing workforce analytics strategy, predictive models, dashboards, KPI frameworks, and data governance. Advise executive leadership on talent strategy, organizational health, workforce planning, and organizational design. Establish people-data standards, security, access controls, compliance practices, and architecture in partnership with IT and Data Engineering. Translate workforce data into actionable business narratives while mentoring analytics teams and supporting HR initiatives.

Leads the strategy, architecture, and deployment of AI-enabled business intelligence infrastructure. Designs governed semantic layers, data models, and BI systems using dbt and enterprise data warehouses. Manages and coaches a technical engineering team, partners with executives and cross-functional stakeholders, and ensures reliable, high-performing data pipelines, warehouses, and reporting tools. The role also advances AI-driven analytics, data discovery, and self-service reporting across the organization.