Staff Full-Stack Engineer

At Reltio®, we believe data should fuel business success. Reltio's AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our "Customer First", we strive to ensure their success. We embrace our differences and are "Better Together" as One Reltio. We are always looking to "Simplify and Share" our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We "Own It". Every day, we innovate and evolve, so that today is "Always Better Than Yesterday". If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you're ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let's talk!

Job Summary:

As a Staff Full-Stack Engineer at Reltio, you will be a key member of our new Data Quality team, responsible for building a cutting-edge Data Observability platform from scratch. This platform will provide automated profiling and anomaly detection across various data sources, including Cloud Data Warehouses (Snowflake, BigQuery, Databricks, Redshift), dbt, Kafka/streaming, and SaaS applications (SFDC/Dynamics). You will contribute to both the API and UI development, ensuring a robust and intuitive experience. This is an individual contributor role.

Job Duties and Responsibilities:

• Design, develop, and maintain the Data Observability platform using Java for the API
• Implement robust and scalable APIs for seamless integration with various data sources
• Develop intuitive and responsive user interfaces (UI) that provide a comprehensive view of data quality and observability metrics.
• Collaborate with cross-functional teams to define requirements, design solutions, and ensure the successful delivery of the platform.
• Contribute to the entire software development lifecycle, from conceptualization and design to deployment and ongoing maintenance
• Ensure the platform's performance, reliability, and security through rigorous testing and adherence to best practices
• Mentor junior/middle engineers and contribute to a culture of technical excellence and continuous improvement.

Skills You Must Have:

• 7+ years of enterprise software development experience building full-stack platforms
• Experience delivering great experiences with modern UI and UX, given limited guidance
• Proven track record of delivering high-quality enterprise SaaS platforms in a high-stakes environment
• Experience building and delivering APIs for platforms
• Experience delivering SaaS applications that scale and perform with low latency and high throughput
• Strong written and verbal communication skills
• Proven track record of unit and integration testing as a part of your software development processes (CI/CD)

Skills That Are Nice to Have:

• Familiarity with cloud-based development using AWS, Google Cloud Platform (GCP), and/or Microsoft Azure services (such as Lambda, S3, Pub/Sub, Dataflow, or Azure Functions)
• Background in Data Quality systems, frameworks, or tools (e.g., profiling, validation, monitoring)
• Experience or understanding of Master Data Management (MDM) concepts, data modeling, and enterprise data integration patterns
• Experience working with AI and automation tools to improve productivity and delivery speed (GitHub Copilot, Claude Code, Cursor, VSCode Kilo Code, etc.)
• Exposure to containerization and orchestration technologies (Docker, Kubernetes)
• Familiarity with monitoring and observability stacks (Mezmo, Grafana, etc.)