Role Description We are seeking an experienced Senior Data Engineer to design, build, and scale modern cloud-based data platforms that enable trusted analytics, operational reporting, and data-driven decision making across the organization. This role will play a critical part in evolving our data architecture, data engineering practices, and analytics capabilities, with a strong focus on Snowflake as the core enterprise data platform. As a senior member of the data team, you will be responsible for: - Building robust and scalable data pipelines - Optimizing data models - Improving data quality and governance - Enabling self-service analytics capabilities for business and engineering stakeholders The ideal candidate combines strong technical depth in modern data engineering practices with a pragmatic mindset, excellent stakeholder engagement skills, and a passion for building reliable and scalable data platforms. Qualifications - 5+ years of experience in Data Engineering, Analytics Engineering, or related data platform roles - Strong hands-on expertise with Snowflake in enterprise-scale environments - Advanced SQL skills with experience optimizing complex analytical queries and data transformations - Strong analytical, troubleshooting, and problem-solving capabilities - Excellent communication and stakeholder engagement skills - Ability to work effectively in fast-paced, agile, and collaborative environments Requirements - Experience designing and supporting multi-region and enterprise-scale data platform architectures - Strong experience driving performance optimization and cloud cost efficiency initiatives across large-scale data workloads - Experience implementing advanced governance, security, access control, and data protection models within enterprise data platforms - Strong capability in developing architectural standards, engineering documentation, and scalable platform design patterns - Experience working with cloud platforms such as AWS, Azure, or GCP - Experience with data transformation and orchestration tools such as dbt, Airflow, Fivetran, Matillion, or equivalent platforms - Proven ability to manage large and complex datasets in production environments Benefits - Flexibility in work hours and location, with a focus on managing energy rather than time - Access to online learning platforms and a budget for professional development - A collaborative, no-silos environment, encouraging learning and growth across teams - A dynamic social culture with team lunches, social events, and opportunities for creative input - Health insurance - Leave Benefits - 13th Month Salary

Role Description Provides leadership for the Data Integrity Team within Adventist Health. Monitors compliance with enterprise data integrity standards to ensure accurate, consistent, and reliable data. Develops procedures and workflows and ensures high quality of service. Guides Data Integrity Team in the management of the Enterprise Master Person Index, including duplicate records, overlays and all operations within the department. Monitors staff performance and data quality, taking proactive actions to ensure compliance with departmental goals and enterprise data standards. Provides timely feedback to encourage success, ensure accountability, and accomplish recognition. Delegates and assigns work appropriately. Identifies associate and team priorities based on business direction and adjusts when needed. Leads by example and shares knowledge and experiences with associates and team. Creates a respectful work environment with advocacy for team, accountability, and recognition for accomplishment. Identifies the right talent to achieve the desired results; promotes and builds a diverse and cohesive team to accomplish objectives and align associates’ skills to fill gaps. Qualifications - Bachelor's Degree or equivalent combination of education/related experience: Required - Master's Degree: Preferred - Experience in data integrity principles, governance frameworks, data cleaning, and strategic data decision-making: Preferred - Five years' related experience: Preferred - One year leadership experience: Required Requirements - Current permanent U.S work authorization: Required Essential Functions - Leads the Data Integrity Team in the operations of daily job responsibilities. - Develops, recommends, and oversees the implementation and administration of policies and procedures related to the respective area. - Leverages comprehensive knowledge of data integrity practices and procedures to manage enterprise-wide projects. - Coordinates with management team to evaluate and develop effective workflows that adhere to federal, state, and local laws and regulations. - Demonstrates, through plans and actions, a consistent standard of excellence to which all department work is expected to conform. - Conducts recurring quality assurance audits and provides coaching sessions/performance reviews in relation to established benchmarks. - Ensures workflows and team members are timely addressing any and all requests in accordance with industry standards. - Focuses on continuous improvement, working with leadership across the health system with a goal of providing the highest quality service possible. - Provides support for Human Resource guidance. - Completes, reviews, manages, and monitors department budget. - Performs other job-related duties as assigned. Organizational Requirements - Adventist Health is committed to the safety and wellbeing of our associates and patients. Therefore, we require that all associates receive all required vaccinations as a condition of employment and annually thereafter, where applicable. Medical and religious exemptions may apply. - Adventist Health participates in E-Verify. Visit https://adventisthealth.org/careers/everify/ for more information about E-Verify. By choosing to apply, you acknowledge that you have accessed and read the E-Verify Participation and Right to Work notices and understand the contents therein.

• Lead the vision, strategy, and roadmap for Natera’s health system data sharing initiatives, including platforms that integrate Natera’s genomic data with health system clinical data to enable advanced analytics, clinical insights, and operational intelligence. • Identify and prioritize high-value opportunities for secure data exchange, interoperability, and analytics across health systems, including use cases that support clinical decision-making, research, and population health. • Collaborate with engineering, data science, and design teams to define product requirements (PRDs, user stories, user flows) and deliver scalable, high-quality data platform, analytics, and AI-driven insights solutions. • Develop products and user experiences that enable clinicians and health systems to derive insights and actions from combined genomic and clinical datasets, including dashboards, workflow integrations, and AI-assisted recommendations. • Evaluate and integrate third-party technologies (e.g., data interoperability frameworks, analytics platforms, and AI/ML tools) to accelerate development and improve performance. • Develop and track success metrics (e.g., adoption, data utilization, clinical impact, performance, and partner satisfaction) to measure impact and identify continuous improvement opportunities. • Partner with health system stakeholders, clinical informatics teams, and business leaders to ensure seamless integration into clinical workflows and EMR ecosystems.

• Design, configure, and maintain AI agent workflows using Cursor and Claude Code, including structured markdown-based instruction files, slash commands, and agent workflows that implement your architecture automatically. • Research and evaluate new approaches to agent orchestration, identifying where the current system can be made faster, more reliable, or more scalable. • Continuously question existing processes and propose improvements. This is expected, not exceptional. • Guide and review AI-generated code with a critical eye; you are the architect, the agents are the executors. • Build and maintain a RAW → Base → Data Marts pipeline using dbt Core, implementing business logic at the transformation layer. • Own data pipelines end to end, from API ingestion through incremental strategy, transformation, and QA, with full accountability for architectural decisions. • Write and maintain tests and documentation at every layer of the pipeline. • Connect to and pull data from marketing and e-commerce APIs including Meta, TikTok, Shopify, and Klaviyo. • Build comprehensive test suites using Great Expectations or equivalent tooling. • Implement business logic validation checks and automated quality monitoring across the pipeline. • Manually inspect data at the table level, not only through automated scripts, before presenting any conclusions. • Verify your own work as a default behavior, not a step that needs to be requested. • Implement complex business logic and data validation in Python. • Build ETL scripts, automation workflows, and API integration scripts. • Write code that is built to scale, not just to solve the immediate problem.