Top Data & Analytics Jobs in Oklahoma City, OK

Maintain and configure client coding and reporting tables, audit accruals, create and transmit standard and government reports, update coding to ensure payroll/PSL data consistency, and define client requirements for custom reporting while collaborating with clients and internal teams.

Design, build, and maintain ETL/ELT pipelines and analytics data models from structured and event-level data. Transform clickstream/telemetry into user-level journeys, implement dbt transformations in a cloud warehouse (Redshift/Snowflake/BigQuery), develop reverse ETL workflows, enforce CI/CD/version control and automated data quality tests, and partner with BI, marketing, and product to deliver dashboards and attribution reporting.

Lead healthcare payment integrity analyses, collaborate with clients and internal teams, build and maintain large-scale SQL and Spark queries, design ETL/ELT transformations, implement AI/LLM-driven analytical workflows, perform data quality monitoring, and mentor analysts while documenting lineage and audit-ready methodologies.

Perform end-to-end data analysis and transformation for large-scale P&C insurance datasets. Develop source-to-target mappings, validate and profile data, optimize complex SQL queries, and collaborate with business SMEs and technical teams to ensure data quality, standardization, and accurate technical documentation.

Lead BI architecture and solution design; build and optimize Power BI and Tableau semantic models; write and tune DAX, Power Query, and SQL; architect dimensional data models; define governance, CI/CD, and deployment standards; partner with data engineering; drive self-service BI and mentor BI developers.

Design, build, and optimize scalable ETL/ELT data pipelines using Databricks and cloud platforms. Implement data quality checks, monitor and troubleshoot jobs, audit pipelines for compliance, and collaborate with analysts and business stakeholders to define data models and support reporting.

Lead development of enterprise data and analytics systems using Snowflake and Python. Build and optimize data pipelines on AWS (Lambda, Step Functions, ECS), write advanced SQL, and apply domain knowledge of asset management and financial markets.

Design and maintain a formal analytics data layer (AWS Glue, Athena/Presto, LookML); build data models, pipelines, and automated quality checks; investigate anomalies; document metrics and lineage; mentor analytics team members and promote best practices.

Analyze large pharmacy, Medicaid, and Medicare datasets to produce actionable insights. Build and maintain dashboards and visualizations, investigate trends and root causes, recommend process improvements, partner with cross-functional teams, ensure data integrity, and influence strategy through data-driven recommendations to improve pharmacy operations and member experience.

Lead collection, integration, analysis, and transformation of encounter data to improve submission accuracy, compliance, and operational performance. Build scalable analytics and automation using Python, SQL, Databricks, and Power BI; perform root-cause analysis, translate business needs, optimize workflows, and mentor team members.

Lead design and scaling of ELT pipelines and analytics schemas on Snowflake. Build Looker views, CI/CD automation, and orchestration workflows (Prefect/Airflow). Ensure production reliability with monitoring (Datadog, Monte Carlo), partner with cross-functional teams, and provide technical leadership including code reviews, testing, and end-to-end ownership of data integrity and platform trustworthiness.

Build and maintain web crawling and scraping pipelines to collect, transform, and deliver third-party healthcare data. Research sources, assess feasibility, implement extraction strategies, test for quality, and maintain scrapers when sources change. Participate in weekly standups and initial fundraising activity.

Design, build, and maintain cloud-native ETL/data pipelines using Databricks and AWS Glue. Ingest and transform structured and semi-structured data with PySpark, Python, and SQL. Integrate sources including MongoDB, implement data quality checks, optimize pipeline performance, and support production deployments, monitoring, and troubleshooting while collaborating with architects and analysts.

Design, build, and operate large-scale batch and streaming ingestion pipelines, medallion/lakehouse layering, identity resolution and golden-record consolidation, data-quality gates and reconciliation, source-to-canonical mappings and crosswalks, schema enforcement, and observability for client onboarding and production data flows.

Deliver advanced SQL analyses, build and maintain dashboards and recurring reports, define KPIs, translate findings into executive-ready recommendations, partner cross-functionally, and support automation and reporting improvements.