Top Remote Data & Analytics Jobs in Oklahoma City, OK

Designs and operates an AWS-native lakehouse supporting analytics, reporting, visualization, and AI/ML. Builds batch and streaming ingestion pipelines using Python and PySpark, Apache Iceberg data structures, governance and metadata services, quality controls, security, observability, and CI/CD automation. Optimizes performance, scalability, reliability, and cost while collaborating with cross-functional technical teams and documenting architecture, operations, and secure configurations.

Administers, designs, secures, monitors, and optimizes large-scale client/server databases. Responsibilities include database programming, performance tuning, backup and disaster recovery, access control, auditing, documentation, systems integration, and advising users. The role requires supporting database projects in large organizations, working across operating systems and cloud platforms, and maintaining sensitive data security. A Secret clearance and DoD IAT Level II certification are required.

Lead enterprise data architecture for Privia Health’s Snowflake platform, defining scalable modeling, integration, governance, security, and optimization standards. Design Medallion Architecture layers and healthcare data schemas spanning EMRs, claims, eligibility, and value-based care data. Establish dbt, Python, testing, orchestration, and CI/CD best practices; enforce HIPAA, PHI/PII masking, access controls, lineage, and cataloging. Provide technical leadership, design reviews, mentorship, and cross-functional guidance to engineering, analytics, clinical, and product stakeholders.

Designs and maintains data warehouses, semantic models, metrics layers, pipelines, dashboards, and certified datasets. Establishes KPI governance, data security, row-level access controls, quality standards, and observability. Builds Sigma, Power BI, and Databricks dashboards, supports self-service analytics, resolves BI issues, and enables AI/ML use cases. Collaborates with architecture, engineering, analysts, and business stakeholders to define requirements, document solutions, train users, and drive BI adoption.

Own and enhance Sigma dashboards and business intelligence reporting for the Records Retrieval business. Partner with stakeholders to translate business needs into scalable data solutions, analyze complex datasets, improve data quality and governance, define reporting standards, and support Snowflake data warehouse and modeling initiatives. Deliver actionable insights, automate reporting processes, evaluate analytics tools, and independently drive analytics projects from requirements through delivery.

Loads, queries, extracts, validates, and refreshes client data; prepares reports and deliverables; identifies automation and process-improvement opportunities; supports UAT, system implementations, and quality assurance testing; and collaborates with cross-functional teams. The role translates client requirements into actionable tasks and requires SQL, relational database, Oracle, Unix, data analysis, reporting, and communication skills.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.