Role Description Join us to start Caring. Connecting. Growing together. You’ll enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges. - Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on the responsible use of AI. - Architect and optimize complex ETL processes and data pipelines using Databricks (Spark, SQL, Python) or other enterprise-scale integration tools to ensure high-performance processing of large-scale datasets. - Evaluate emerging trends in ETL frameworks and AI to inform solution design and drive strategic innovation within the analytics platform. - Use enterprise-approved AI tools to automate data engineering workflows, streamline ETL maintenance, and drive continuous improvement in engineering velocity. - Implement advanced data modeling techniques, such as star schemas and incremental loads, to ensure data integrity and scalability across all ETL layers. - Build and maintain executive-level dashboards and semantic models in Power BI, ensuring seamless data flow from backend ETL processes to end-user visualizations. - Partner with product and business leaders to translate complex business requirements into robust, automated data integration solutions. - Lead technical coordination within a global delivery model, ensuring consistency and quality of ETL standards across onshore and offshore teams. Qualifications - Bachelor's degree or equivalent experience. - 6+ years of experience in analytics engineering, business intelligence, or data engineering roles delivering enterprise-scale analytics solutions. - 5+ years of Cloud experience (Azure, GCP, AWS, or OCI). - 5+ years of experience in programming languages such as Python, Java, etc. - 4+ years of hands-on experience using Databricks (Spark, SQL, Python, notebooks) or other major ETL platforms to build and optimize large-scale data pipelines. - 4+ years of experience in data modeling (star schemas, semantic modeling, incremental loads, large datasets) and advanced SQL. - 1+ years of experience delivering AI-driven analytics or data solutions. Requirements - Healthcare industry experience, specifically in clinical or real-time analytics. - Experience with ETL orchestration tools (e.g., Airflow, Azure Data Factory) and managing data lineage in governed environments. - Experience developing AI-driven automations or integrating large language models (LLMs) into data products and ETL workflows. - Experience with Power BI, Tableau or other visualization tools, including advanced DAX, Power Query, and semantic modeling. - Demonstrated experience working in global delivery models with effective onshore-offshore collaboration. - Proven ability to solve complex technical problems with a focus on data processing efficiency and system scalability. Benefits - Comprehensive benefits package. - Incentive and recognition programs. - Equity stock purchase. - 401k contribution (all benefits are subject to eligibility requirements).

Role Description Are you passionate about building modern, scalable data platforms that power enterprise analytics? We're looking for a Senior Data Engineer to play a key role in the global implementation and ongoing evolution of our Databricks data platform. This is an exciting opportunity to shape the foundation of our enterprise data strategy while mentoring a growing team of engineers and partnering with stakeholders around the world. As a Senior Data Engineer, you'll serve as one of the technical leaders on our Data Platform team, helping design, implement, and optimize enterprise-scale data solutions that enable business intelligence, advanced analytics, and AI initiatives. In this role, you will: - Lead the implementation and continued enhancement of our global Databricks data platform. - Design, build, and optimize scalable ETL/ELT pipelines for structured and semi-structured data. - Develop modern data models, data warehouses, and data marts to support enterprise analytics. - Collaborate closely with data scientists, analysts, business partners, and IT teams to translate business requirements into scalable technical solutions. - Improve data quality, governance, security, and platform reliability. - Optimize data workflows for performance, scalability, and cost efficiency. - Provide technical mentorship to junior and mid-level data engineers while helping establish engineering best practices. Qualifications - Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field required. - 5+ years of hands-on experience with SQL and Python. - 5+ years of experience working with cloud platforms (Azure, AWS, or GCP). - 5+ years of experience with modern data warehousing technologies such as Databricks, Snowflake, Redshift, or BigQuery. - Strong experience designing and building enterprise-scale data pipelines and ETL/ELT solutions. - Solid understanding of data modeling, governance, and security principles. - Excellent communication skills with the ability to collaborate across technical and business teams. Requirements - Databricks Certification (preferred). - Experience with Spark, Kafka, or other distributed processing frameworks (preferred). - Experience with DevOps and CI/CD practices (preferred). - Experience supporting machine learning and AI data initiatives (preferred). Benefits - This is more than a traditional data engineering role—it's an opportunity to help build the next generation of our global data platform. - You'll join a growing Data Platform team where you'll: - Lead enterprise-wide Databricks initiatives. - Work alongside a collaborative team while mentoring developing engineers. - Influence technical direction and engineering best practices. - Partner with business leaders across Finance, Sales, Supply Chain, Manufacturing, and Corporate functions. - Help drive digital transformation across a global organization. The salary range for this position is $110,200-$144,700. Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.

Role Description The Principal Databricks Architect will shape and scale our Databricks-based data science and AI platform, and to lead where our practice is heading: a governed, self-service environment that lets data science teams move from idea to production with minimal friction. As the technical leader of the platform, this individual brings design thinking to mature the platform as a product—designing reusable capabilities, patterns, and guardrails that empower actuarial, data science, and analytics teams to independently develop, train, deploy, and operate models and AI agents. The ideal candidate pairs deep architectural expertise with a strong enablement mindset, engaging directly with diverse data science communities to understand their workflows and remove barriers to adoption. They will modernize our platform around the latest Databricks capabilities—Unity Catalog governance, Mosaic AI and Agent Bricks, Genie, Lakeflow, and Lakebase—while ensuring interoperability with our Snowflake enterprise data platform through open formats such as Apache Iceberg. This is a highly visible role that sets technical direction, champions frictionless developer experience, enforces least-privileged access and data governance, and enables global, cost-efficient deployment of AI in compliance with data sovereignty requirements. Qualifications - Bachelor’s Degree in Arts/Sciences (BA/BS) Computer Science or equivalent education and experience - Required - 10+ years progressive experience in enterprise-level IT functions - Required - 7+ years experience in managing large enterprise data initiatives and teams - Required - 5+ years architecting and operating enterprise-grade data and AI/ML platforms, with hands-on Databricks and Apache Spark experience on a major cloud (AWS preferred; Azure or GCP) - Required Requirements - Modern Databricks Expertise: Deep knowledge of the Databricks Data Intelligence Platform—Unity Catalog, Delta Lake/Iceberg, Lakeflow/Delta Live Tables, MLflow, Model Serving, AI Agent Framework/Agent Bricks, Lakebase, and Genie—plus lakehouse architecture, ETL/ELT, and infrastructure-as-code (Terraform, Databricks Asset Bundles) - Required - Data Science Enablement: Demonstrated success building self-service platform capabilities and developer experiences that empower data science teams, along with a ModelOps track record covering lifecycle management, versioning, governance, and deployment automation - Required - Consulting & Communication: Strong consulting, stakeholder management, and communication skills, with a track record of influencing senior leadership and driving technology adoption - Required - Innovation & Initiative: Demonstrated ability to drive innovation, introduce contemporary practices, and lead technology transformations - Required - Thought Leadership: Ability to define and communicate architecture vision, roadmaps, and best practices to both technical and non-technical audiences - Preferred - Continuous Improvement: Passion for learning, sharing knowledge, and staying ahead of industry trends in data and AI - Preferred - Platform-as-a-Product Mindset: Passion for delivering frictionless, self-service experiences and measurable business value—treating internal data science teams as customers and continuously improving their journey from prototype to production - Preferred - Interoperability Experience: Familiarity integrating Databricks with Snowflake and other engines via open standards (Apache Iceberg, Unity Catalog/Lakehouse federation) to minimize data duplication and governance gaps - Preferred - Availability for cross-time-zone meetings - Preferred Benefits - Gain valuable knowledge from and experience with diverse, caring colleagues around the world. - Enjoy a respectful, welcoming environment that fosters individuality and encourages pioneering thought. - Join the bright and creative minds of RGA, and experience vast, endless career potential. - Compensation Range: $126,710.00 - $188,840.00 Annual - Annual bonus plan and eligibility for long-term equity incentive plan. - Full range of health, retirement, and other employee benefits.

Role Description The Big Data Data Modeller plays a crucial role in designing, implementing, and maintaining data models for big data systems, ensuring efficient data processing and analysis. - Design and develop data models for big data applications. - Collaborate with data engineers and data scientists to optimize data storage and retrieval. - Implement data quality checks to ensure accuracy and reliability of data. - Evaluate and recommend data modeling techniques and tools for optimal performance. - Troubleshoot data modeling issues and provide timely resolutions. - Stay updated on emerging trends and technologies in big data modeling. - Design, extend, and govern ontologies in OWL; develop schema, patterns, and modular models for reuse and scale. - Author SPARQL queries for data access, analytics enablement, and quality checks. - Define SHACL shapes for data validation; integrate validation into CI/CD and pipeline checkpoints. - Work with product owners and SMEs to convert competency questions and business requirements into semantic models and graph queries. - Curate and harmonize biomedical vocabularies (e.g., OBO Foundry, SIO, EBI) and align with enterprise data mappings. - Collaborate with data engineers to implement pipelines (e.g., Pandas, PySpark) for semantic enrichment, mapping, validation, and graph/warehouse loads. - Create and maintain semantic data dictionaries for mapping and transformation design and integrate with platforms such as Snowflake or Databricks when applicable. - Establish modeling guidelines, review processes, and versioning with Git. - Develop reference implementations, standards, and enablement artifacts for broader reusability. - Lead client workshops, solution design, and incremental delivery. - Mentor junior team members and contribute to proposals, POVs, and accelerators. Qualifications - Bachelors - Business Analytics - Bachelors - Computer Science - Bachelors - Statistics - Masters - Data Science Requirements - Hands-on expertise with OWL, SPARQL, and SHACL (portfolio, repos, or samples welcome). - Proven experience applying biomedical ontologies; strong plus for OBO Foundry resources and SIO. - Proficiency with Python for data wrangling and pipeline integration; familiarity with CI/CD and Git workflows. - Demonstrated ability to translate business questions into semantic models and graph queries. - Strong consulting skills: stakeholder engagement, solution storytelling, and workshop facilitation. Benefits - Lead AI-powered transformation – Drive innovation and solve real-world business challenges that matter. - Make an impact – Help global enterprises solve business challenges that matter. - Accelerate your career – Gain hands-on experience, mentorship, and world-class learning opportunities to stay ahead. - Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day. - Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress.