Lead Data Developer

SCA Health•UNAVAILABLE, UNAVAILABLE

About The Position

The Lead Data Developer is a senior individual contributor and technical leader responsible for designing, delivering, and evolving enterprise data platforms and solutions that support clinical, operational, and financial outcomes across SCA Health. This is not a formal people-management position. The role serves as technical owner and delivery lead, coordinating technical resources in partnership with resource managers and influencing priorities across distributed teams, including offshore resources. The Lead Data Developer works across legacy and cloud-based technologies and supports SCA Health’s cloud-first and AI-enabled data strategy. The role owns solution architecture, design quality, delivery outcomes, and maintainability; leads data engineering and platform development; supports cloud transformation; and incorporates AI/ML capabilities into data pipelines and products. It also requires attention to HIPAA and enterprise security and governance standards, close stakeholder collaboration, mentoring, and participation throughout the full product lifecycle, from ideation through production support and decommissioning.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent experience.
At least 8 years of experience in data engineering, data platform development, or related disciplines.
Experience serving as a technical lead or technical owner for complex initiatives.
Ability to lead cross-functional teams without formal authority.
Experience delivering large-scale data integration and transformation solutions.
Demonstrated application of an AI-first mindset, incorporating AI/ML capabilities into data platform design, engineering practices, and solution delivery.
Experience with Microsoft data and cloud technologies, including Azure and the SQL Server ecosystem.
Experience with Snowflake, Airflow, and dbt.
Experience designing and developing ETL/ELT across complex data environments.
Experience with relational and dimensional data modeling.
Experience with CI/CD and DevOps practices, including Azure DevOps and GitHub Enterprise.
Hands-on experience implementing AI/ML capabilities in data platforms or products.
Experience supporting or leading on-premises-to-cloud transformation initiatives.
Experience implementing data security controls for PHI/PII in regulated environments, such as HIPAA or equivalent.
Strong analytical and problem-solving skills.
Excellent verbal and written communication skills.
Ability to work effectively in a remote and distributed team environment.
Ability to manage competing priorities and deliver outcomes.
Strong collaboration and stakeholder engagement skills.
Demonstrates accountability, professionalism, and integrity; leads with a solution-oriented mindset; communicates clearly; mentors others; and works independently while remaining aligned with broader team goals.

Nice To Haves

Healthcare data domain experience, including clinical, operational, or financial data.
Experience with Azure Synapse, Databricks, or similar advanced platforms.
Experience with Kubernetes or containerized environments.
Experience with ServiceNow integrations.
Relevant Microsoft or cloud/data certifications.

Responsibilities

Serve as technical owner for assigned initiatives, accountable for architecture, design quality, delivery outcomes, and long-term maintainability.
Lead and coordinate the design, development, testing, deployment, and support of data solutions.
Partner with resource managers to align staffing, skillsets, and priorities with delivery needs.
Direct technical execution across assigned team members and ensure alignment with standards and timelines.
Clarify requirements, resolve ambiguity, provide accurate estimates, and deliver reliable solutions.
Design and implement scalable hybrid and cloud-first data architectures.
Lead or contribute to phased transformation of on-premises data platforms to cloud-based solutions.
Partner with Enterprise Architecture to define solution strategies aligned with business and technology roadmaps.
Promote reusable engineering patterns and framework-driven development while balancing legacy support and modernization.
Architect and develop enterprise data pipelines and platforms using the specified Azure, Snowflake, Airflow, dbt, and SQL Server technologies.
Ensure data solutions meet standards for performance, scalability, reliability, and observability; implement monitoring, logging, and operational readiness capabilities.
Design and implement AI/ML-enabled data capabilities, identify automation, predictive analytics, and intelligent workflow use cases, and align initiatives with measurable business value.
Ensure AI-enabled solutions are production-ready, scalable, and maintainable.
Ensure compliance with HIPAA and enterprise data security and governance standards.
Implement access controls, encryption, and auditability for PHI/PII data.
Participate in code reviews, change management, and release management, and use ServiceNow for incident, request, and operational management.
Partner with business stakeholders to understand requirements and prioritize delivery; collaborate with Enterprise Architects, Product Owners, and cross-functional teams.
Facilitate technical design discussions and solution alignment sessions, and communicate technical concepts to technical and non-technical audiences.
Mentor junior and mid-level data developers and promote coding, architecture, and documentation best practices.
Support accountability, collaboration, and continuous improvement.
Participate in the full product lifecycle, including ideation, design and development, deployment and release, production support and optimization, and decommissioning.
Maintain current technical and operational documentation and ensure solutions are supportable and aligned with long-term platform strategy.