Staff Data Engineer, Data Platform - IntelliScript

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Engineer, Data Platform - IntelliScript based in United States.

As a Staff Data Engineer, you will serve as a technical leader shaping the architecture, scalability, security, and performance of an enterprise data platform. You will guide strategic decisions across data engineering while building modern warehouse, lakehouse, pipeline, and data product solutions. The role focuses heavily on healthcare data, requiring strong expertise in clinical standards, governance, privacy, and large-scale data management. You will work across hybrid cloud environments, using technologies such as Databricks, AWS, Terraform, Python, SQL, and Delta Live Tables. You will partner with engineering, data science, analytics, development, and business teams to translate complex requirements into reliable and secure solutions. As a senior technical voice, you will influence architecture, mentor engineers, drive innovation, and ensure technology investments deliver measurable business value.

Accountabilities: Act as a subject matter expert and thought leader for the Data Platform domain, providing technical guidance and influencing architecture and engineering decisions.

Define and advance data engineering strategy, including approaches for moving, storing, processing, governing, and maintaining high-quality enterprise data.

Lead complex data platform initiatives by coordinating teams, managing timelines, communicating progress, and aligning technical execution with strategic business objectives.

Expand and optimize enterprise data warehouses and lakehouse environments supporting healthcare-focused data products and internal use cases.

Establish and maintain data governance capabilities, including Unity Catalog configuration, data lineage, data quality, auditability, stewardship, and compliance with evolving industry standards.

Design and implement data security practices for identified and de-identified PHI and PII, consistently applying least-privilege access principles.

Build reliable external data products that meet high standards for data quality, performance, scalability, security, and operational reliability.

Develop ETL and transformation solutions using Delta Live Tables, automation, SQL, Python, Scala, and cloud-based big data technologies.

Design performant enterprise medallion architectures and fit-for-purpose batch and near-real-time streaming solutions.

Architect solutions for large, diverse structured and unstructured healthcare datasets used by both internal and external stakeholders.

Build platform infrastructure using Infrastructure as Code practices, including Terraform, Asset Bundles, and GitHub-based development workflows.

Partner with business stakeholders to design cost-effective and transparent data solutions while balancing performance, scalability, security, and operational requirements.

Architect, build, maintain, monitor, and optimize scalable data pipelines and ETL infrastructure across diverse data sources.

Work with migration and integration technologies such as Fivetran, AWS services, and custom data ingestion solutions.

Design reliable event-driven data processing and effective pipeline monitoring capabilities to improve resilience and operational visibility.

Design and implement internal APIs that enable data integration across systems and applications.

Develop APIs that allow internal systems to consume datasets and capabilities from Databricks, while integrating with external platforms such as Salesforce, financial systems, HR systems, and other business applications.

Lead the design, implementation, and maintenance of standards-based data models for structured and unstructured data, including healthcare standards such as FHIR and OMOP.

Assemble complex datasets that satisfy functional and non-functional requirements while ensuring models align with business objectives and data privacy regulations.

Collaborate with data engineering, software development, analytics, data science, clinical, and business teams to gather requirements and deliver meaningful data solutions.

Translate complex technical concepts into clear guidance for non-technical stakeholders and advise teams on appropriate data engineering and architectural practices.

Develop project plans, estimate implementation efforts, and ensure technology execution remains aligned with business strategy.

Identify and implement process improvements through automation, infrastructure redesign, optimized data delivery, and scalable engineering practices.

Build analytics and data tools that provide actionable insights into operational performance and support clinical, analytics, and data science teams.

Evaluate emerging technologies, investigate new tooling, develop implementation plans, and lead the deployment of solutions that improve platform capabilities.

Mentor and guide engineers on emerging technologies while leading through influence, technical expertise, and strategic collaboration.

Requirements

At least 15 years of relevant experience designing, developing, and testing enterprise Data Platform solutions, including data warehouses, data lakes, and data products.

Expert-level experience with Databricks and AWS.

Expert knowledge of relational and non-relational databases, including technologies such as SQL Server, PostgreSQL, DynamoDB, and DocumentDB.

Demonstrated experience managing and standardizing clinical data from both structured and unstructured sources.

Extensive experience building, deploying, and managing data solutions within AWS environments.

Expert knowledge of healthcare data standards, including FHIR, C-CDA, and traditional HL7.

Expert knowledge of clinical standards and ontologies such as ICD-10, SNOMED, NDC, LOINC, and RxNorm.

Expert capability in data modeling, enterprise data warehouse architecture, data lake design, and data product development.

Strong experience designing and building APIs, ETL frameworks, data ingestion processes, and supporting enterprise data solutions.

Experience with performance tuning, query optimization, data security, monitoring, and release management.

Proven ability to work with large, disparate datasets, including identified and de-identified healthcare data from multiple sources.

Experience implementing Infrastructure as Code using Terraform, Asset Bundles, and GitHub.

Experience collaborating with Data Science teams and developing or supporting AI-based solutions that generate operational efficiencies and business value.

Strong communication and collaboration skills across technical and non-technical disciplines.

Ability to navigate ambiguity, identify practical solutions, and balance strategic priorities with tactical execution.

Demonstrated ability to teach, mentor, and influence engineering teams on new and emerging technologies.

Customer-focused and business-oriented approach, with the ability to connect technical decisions to measurable organizational outcomes.

Self-directed, thorough, driven, and comfortable taking ownership of complex technical initiatives.

Strong influencing and persuasion skills, with the ability to lead without relying solely on formal authority.

Curiosity about emerging industry trends and a commitment to selecting fit-for-purpose technologies and approaches.

Bachelor’s or master’s degree in Computer Science, Data Engineering, or a related field is preferred.

Experience within the health insurance or life insurance industry is preferred.

Professional-level AWS solution architecture certification is a plus.

Willingness to travel to a company office in Brookfield, Wisconsin, as needed, as well as travel nationally for meetings, conferences, and team events.

Benefits

Annual salary range of $131,600 to $249,780 , depending on qualifications, experience, location, skills, certifications, and other relevant factors.

For candidates residing in Alaska, California, Connecticut, Illinois, Maryland, Massachusetts, New Jersey, New York City, Pennsylvania, Virginia, Washington, or Washington, D.C., the salary range is $151,340 to $249,780 .

For candidates in other U.S. locations, the salary range is $131,600 to $217,200 .

Remote work opportunity available anywhere in the United States.

Medical, dental, and vision coverage for employees, dependents, and domestic partners.

Employee Assistance Program providing confidential personal and work-related support.

401(k) plan with company matching and profit-sharing contributions.

Discretionary bonus program recognizing employee contributions.

Flexible Spending Accounts for eligible medical, dependent care, transportation, and other qualified expenses.

Paid time off beginning on the first day of employment, with full-time employees accruing 15 days annually.

At least 10 paid holidays per year.

Family-building benefits, including adoption and fertility assistance.

Up to 11 weeks of paid parental leave for eligible employees.

Employer-paid life insurance and AD&D coverage.

Employer-paid short-term and long-term disability coverage.

Access to learning, mentoring, professional development, and skills training opportunities.

Opportunity to influence enterprise data strategy and work with modern cloud, lakehouse, AI, and healthcare data technologies.

High-impact technical leadership role with significant autonomy, cross-functional exposure, and opportunities to mentor and influence engineering teams.

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