Remote Data Jobs • Data Governance

As a Data Management Consultant, you will guide organizations in designing and implementing governance frameworks, policies, and technology to ensure high-quality, well-managed, compliant, and accessible data across the organization, blending deep technical knowledge of data architecture to equip you to advise, facilitate, and lead cross-functional teams.

Manages and maintains databases supporting Social Security Administration learning management systems and training platforms. Ensures data integrity, security, and optimal performance of training-related databases while implementing backup and recovery procedures. Supports data analytics and reporting requirements for training program evaluation and compliance.

Lead the design and implementation of cutting-edge data architectures that elevate business operations and play a pivotal role in shaping the data landscapes of our diverse range of clients. Work closely with cross-functional teams, analyze business requirements, strategize data solutions, and execute designs that optimize data storage, integration, and accessibility.

As a Data Architect, you will be at the forefront of designing and architecting comprehensive data solutions across multiple platforms aligned with client needs and objectives. Lead data architecture transformations and/or migration to modern cloud solutions, ensuring robustness and scalability of the solution. Design efficient, scalable ETL/ELT pipelines that streamline data processing and integration.

We are seeking a Snowflake Data Analyst with strong SQL and ETL expertise to design, manage, and optimize our Snowflake environment. This role will play a critical part in enabling secure, accurate, and business-aligned data access across the client and downstream systems. The ideal candidate will bring a blend of Snowflake platform skills, ETL integration experience, and business collaboration to support data-driven decision-making.

This position plays a lead role in building and maintaining the Snowflake data warehouse environment, designing scalable ETL pipelines, and ensuring secure, efficient access to institutional data. The Data Engineer will collaborate closely with software engineers, institutional research, and the Office of Innovation and Enhancement to deliver reliable data solutions that support analytics, reporting, and strategic decision-making across the University.

Drive AKKO's analysis and reporting capabilities by owning metrics, data collection, cleaning, and understanding patterns/anomalies. Design impactful reports, solve complex data challenges, and have the freedom to implement your own ideas, including building AI/ML models. You will conduct analysis to uncover trends, patterns, and opportunities for improving business performance and customer and partner experience.

We're looking for our first Principal Data Engineer to design, build, and own our data ecosystem from the ground up. This role provides a unique opportunity to lay the foundation for our entire data strategy and directly influence how we use data to drive decisions across the company and build data-driven product capabilities. You'll be a hands-on developer and a strategic partner, collaborating with leadership and engineering teams to turn raw data into a valuable asset.

Lead and transform our organization's data and analytics capabilities by developing and executing an integrated Data, Analytics, and AI strategy that accelerates commercial growth, drives business value, ensures data governance, and encourages collaboration across regions. This position will deliver innovative, data-driven solutions that enhance customer experience and boost market performance.

Lead the vision for a modern, scalable, and governed data ecosystem. Serve as a technical leader and strategic partner, driving enterprise data architecture decisions while remaining hands-on in building and optimizing key components of our data platform. Lead data architecture strategy across domains and systems, while also actively contributing to the delivery of data models, semantic layers, pipelines, and metadata frameworks.