Top Data & Analytics Jobs in Phoenix, AZ

Owns AML transaction-monitoring models across their lifecycle, including performance monitoring, implementation testing, documentation, revalidation support, issue remediation, and model governance. Analyzes transaction data, model outputs, data quality, thresholds, segmentation, and risk factors using quantitative methods and programming. Partners with technology, data, investigations, Model Risk Management, audit, and leadership to resolve findings and communicate model risks.

Design and develop data pipelines, integrations, transformations, and infrastructure across AWS, Snowflake, Airflow, and MySQL. Troubleshoot warehouse issues, validate data quality, improve pipeline reliability, and translate business needs into data engineering solutions. Interpret technical findings for client recommendations, manage workstreams, review junior team members’ work, and provide technical guidance across managed services engagements.

Designs, builds, optimizes, and supports scalable AWS-based data infrastructure, pipelines, data models, and ETL/ELT processes using Python, SQL, PySpark, Databricks, and Spark. The role supports analytics, reporting, and business intelligence through production monitoring, troubleshooting, testing, CI/CD, documentation, and cross-functional collaboration with BI, Product, Engineering, Data, and client-facing teams.

Provide accurate valuations and risk assessments for single-family homes using internal tools and pricing model outputs. Incorporate local market knowledge, collaborate with sales, homes, data science and engineering to improve pricing operations and ensure competitive, consistent offers.

Owns AirLife’s enterprise Databricks data platform, including architecture, governance, security, cost management, and performance. Leads development of scalable pipelines integrating SAP, Dynamics GP, Salesforce, and other systems into a governed Lakehouse. Establishes data quality, lineage, metadata, and medallion architecture standards while supervising and mentoring the data engineering team. Partners with analytics, AI, supply chain, master data, and FP&A stakeholders to deliver reliable data capabilities.

Analyzes complex automotive data, standardizes datasets and KPI definitions, partners with engineering and governance teams, and develops scalable self-service dashboards. The role translates ambiguous business needs into data requirements, automates digital analytics programs, investigates trends and attributes, and supports enterprise reporting. It requires SQL, Excel, data visualization, statistical analysis, and AI tool experience. The position is hybrid, requiring at least 10 office days monthly, with travel up to 10%.

Leads pricing and product analytics strategy for Auto and Property teams. Develops strategic plans, business cases, analytical frameworks, and outcome measures; evaluates profitability, pricing, risk, marketing, sales, and member experience insights. Influences executive decisions through quantitative and qualitative analysis, storytelling, and stakeholder engagement. Establishes operational processes, tracks initiatives, mentors team members, and ensures compliance with risk policies.

Stewards assigned financial data domains by monitoring data quality, maintaining metadata and lineage, investigating defects, supporting governance and compliance, and partnering with business, product, engineering, risk, and security teams. Uses SQL and data quality tools to validate data flows, identify anomalies, assess impacts, and coordinate remediation. Maintains business glossaries, critical data elements, ownership documentation, and audit evidence while promoting trusted, consistent use of enterprise data assets.

Owns the trust, quality, usability, and regulatory defensibility of wealth data assets. Partners with data product managers, business owners, and engineering teams to define quality standards, manage domain roadmaps, profile data using SQL, investigate anomalies, resolve root causes, validate data flows, implement privacy controls, and support audit readiness. Requires strong private wealth management expertise, data governance experience, technical proficiency, and cross-functional delivery leadership.

Analyzes complex customer, operational, financial, and survey data to identify trends, drivers, risks, and opportunities. Manages the Voice of Customer program, conducts advanced statistical and quantitative analyses, validates data quality, and translates findings into actionable recommendations. Develops executive reporting, narratives, presentations, and visualizations, presents insights to senior leadership, manages vendor and program administration, and partners cross-functionally to improve customer experience, loyalty, retention, and business performance.

Performs complex analysis of consumer product portfolios, financial models, market data, and trends to improve risk, profitability, forecasting, and operational performance. Communicates insights to senior management, mentors peers, supports large-scale platform and integration projects, and collaborates across Risk, Product, and business teams. The role may also manage associates and drive strategic improvements, reporting, process excellence, and data-informed decision-making.