Top Remote Data & Analytics Jobs in Dallas, TX

The Senior Manager-Quality Engineering & Automation will lead quality engineering practices, oversee testing frameworks, manage teams, and promote automation and quality excellence in software delivery.

Design and implement data models and views for integrating legacy systems with ITBA, focusing on managing various data sources and deriving KPIs for scorecards.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.

Lead enterprise data and analytics strategy, operating model, and governance to modernize reporting, build a scalable Azure-based lakehouse platform, standardize semantic models and metrics, enable self-service analytics, and drive AI-enabled productivity. Partner with executives, IT, and business teams to prioritize delivery, manage governance and vendors, and measure business value from analytics initiatives.

The Data Privacy Compliance Analyst will support the development and implementation of data privacy programs, assist privacy operations, and ensure compliance with global privacy laws.

The Data Engineer will design, build, and deploy scalable data solutions, optimize data flows, and implement ETL processes, leveraging various cloud platforms and technologies.

Designs and governs Axiom's enterprise data model, sets data governance and quality standards, manages a Data Engineer, aligns data architecture and AI technology choices with enterprise strategy, administers Databricks, and ensures documented lineage, ownership, and data access for stakeholders.

The Senior Relativity Archiving Analyst is responsible for archiving and purging Relativity workspaces and file shares, documenting processes, and resolving archiving issues.

The Product Analyst will write API specifications, document API functionality, collaborate across teams for data mapping, and analyze API usage for improvement opportunities.

Lead a team of 5-6 data engineers to design and implement scalable data pipelines (Airflow), manage Snowflake data architecture, build real-time streaming solutions with Kafka/Spark Streaming, develop and integrate APIs, enforce code quality, and drive technical decisions and best practices.