Top Data & Analytics Jobs in Tulsa, OK

Build, operate, and improve Tala’s production data synchronization and change data capture pipelines across global markets. Deliver reliable, low-latency data to Snowflake using AWS, Kafka, Spark Structured Streaming, and lakehouse technologies. Improve scalability, performance, cost efficiency, data quality, monitoring, testing, CI/CD, and infrastructure as code. Troubleshoot incidents, lead root-cause analyses, document operational practices, contribute to architecture decisions, and collaborate with data, analytics, product, credit, and business teams.

Build and maintain dbt SQL models, data pipelines, curated datasets, reports, and dashboards supporting state partners, customers, Finance, Operations, and executives. Own external and internal Metabase environments, support the data warehouse, and establish consistent metric definitions across technical and non-technical teams. The role also requires analytics support, stakeholder communication, and experience with Airflow, Python, and Git-based workflows.

Analyzes site performance data, identifies KPI root causes, synthesizes field feedback, and develops actionable recommendations for a multi-year SAP S/4HANA transformation. The role prepares executive reporting for Steering Committee, sponsor, and stage-gate reviews; tracks value realization; designs reporting templates, data models, and recurring tracking mechanisms; and supports leadership decision-making. It partners with field and business stakeholders and may guide analysts without formal supervisory responsibility.

Leads complex analytics initiatives for the Consumer Deposits portfolio, owning Net Present Value methodology and models. Translates ambiguous business questions into scalable datasets, analytical products, and actionable insights supporting pricing, marketing, product, customer, and strategic decisions. Partners with senior stakeholders and cross-functional teams, manages projects independently, improves analytical methodologies and governance, and mentors analysts.

Analyze personal loan product performance, customer behavior, funnel conversion, campaigns, and key performance metrics. Design measurement frameworks, identify tracking gaps, conduct root cause analysis, develop A/B tests, support analytics infrastructure, and create dashboards. Partner with Product, Engineering, Data Science, and Business teams to translate insights into product improvements and increased origination volume.

Lead advanced Amazon and commerce analytics using Amazon Marketing Cloud, advertising, and retail data. Build queries, dashboards, reports, tests, forecasts, and actionable client-ready recommendations. Partner with client, media, operations, data science, and reporting teams to support investment, optimization, and retail decisions. Ensure analytical quality, documentation, automation, and measurement rigor while identifying growth opportunities and communicating technical insights to clients.

The Senior Data Analyst will support Growth and Product teams through paid-channel analysis, user journey optimization, activation and retention insights, and churn reduction. Responsibilities include developing experiments, analyzing ad network performance, improving tracking and instrumentation, ensuring data quality, and enabling self-service analytics. The role requires translating complex data into actionable recommendations and communicating effectively across technical and non-technical teams in a fast-paced SaaS environment.

Owns performance analytics for General Liability claims processes, monitoring trends, diagnosing root causes, evaluating process improvements, and recommending priorities to leadership. Partners cross-functionally with claims, actuarial, underwriting, data, and field operations teams. Presents metrics and action items, validates deployed solutions, supports process optimization, and translates customer and business needs into actionable data-driven solutions.

Design, build, and optimize enterprise ETL/ELT pipelines, cloud data lakes, lakehouse solutions, data models, and semantic layers across AWS and Azure. Ensure data quality, security, performance, reliability, and governance while supporting analytics, reporting, and AI initiatives. Collaborate with product, engineering, IT, and business stakeholders to translate requirements into scalable data solutions, monitor pipeline health, troubleshoot issues, and improve data architecture and practices.

Lead full-cycle customer data migrations from legacy DME/HME systems into a SaaS platform. Responsibilities include mapping, extracting, cleansing, transforming, and validating patient, inventory, claims, order, and payer data; resolving discrepancies; collaborating with implementation and product teams; supporting customers; and documenting migration processes.