About Skypoint
Skypoint is a HITRUST r2–certified Agentic AI platform for healthcare operations, designed to accelerate productivity and operational efficiency across healthcare organizations. Our platform enables healthcare providers, payers, and senior care organizations to unify fragmented data, model industry-specific ontologies, and deploy AI agents that automate workflows and support better, faster decision-making.
Founded in 2020 in Portland, Oregon, Skypoint has grown to a team of over 75 employees and now serves more than 100 customers. We are proud to be recognized on Deloitte’s 2024 and 2025 Technology Fast 500™, celebrating the fastest-growing technology companies in North America, and to be featured on the INC. 5000 list in 2025, reflecting our strong and sustained revenue growth over the past three years.
About the Role
We are looking for an experienced Senior Data & Application Engineer with 5+ years of hands-on engineering experience.
This is not solely a Data Engineering role. It is a Full-Stack Engineering role with a strong focus on data. The ideal candidate should be comfortable working across application development, data engineering, APIs, integrations, backend services, and customer-facing technical requirements.
You will work closely with engineering, product, analytics, and customer-facing teams to build end-to-end solutions that ingest, transform, process, and deliver data across healthcare and enterprise systems.
This is a highly hands-on role requiring strong technical ownership, problem-solving skills, and the ability to interact directly with US-based customers and stakeholders.
Key Responsibilities
Design, build, and maintain scalable ETL/ELT and data processing pipelines for structured and unstructured data.
Develop reliable data ingestion frameworks integrating APIs, databases, files, cloud applications, and third-party systems.
Build and maintain backend services, REST APIs, and application integrations.
Contribute to full-stack application development based on product and customer requirements.
Build and optimize data models, data warehouses, and data lake/lakehouse architectures.
Develop data transformation and processing workflows using Python, SQL, PySpark/Spark, and modern engineering frameworks.
Work with cloud data platforms and technologies such as Snowflake, Databricks, AWS, and Azure.
Build batch and real-time/near-real-time data processing solutions.
Implement data quality checks, validation, monitoring, logging, and alerting.
Optimize applications, pipelines, and queries for performance, scalability, reliability, and cost efficiency.
Troubleshoot complex issues across applications, APIs, source systems, pipelines, integrations, and downstream systems.
Work with Product and Engineering teams on AI, analytics, reporting, and application use cases.
Translate customer and business requirements into scalable technical solutions.
Participate in code reviews and contribute to software engineering standards and best practices.
Mentor junior engineers and provide technical guidance where required.
Collaborate directly with US-based customers and teams for requirement gathering, solution design, troubleshooting, implementation, and delivery.
Required Skills & Experience
5+ years of professional software/data engineering experience.
Strong data engineering expertise combined with the ability and willingness to work on full-stack development.
Advanced proficiency in SQL and Python.
Strong hands-on experience building production-grade ETL/ELT and data integration pipelines.
Experience with Apache Spark/PySpark for large-scale data processing.
Strong experience with Snowflake and/or Databricks.
Experience with AWS or Azure cloud services.
Strong understanding of data warehousing, data lakes/lakehouses, dimensional modeling, and data architecture.
Experience building and consuming REST APIs and integrating databases, SFTP/files, and third-party applications.
Experience developing backend services and application integrations.
Working knowledge of modern front-end/full-stack development concepts and frameworks.
Experience with orchestration tools such as Airflow, Azure Data Factory, AWS Glue, or similar technologies.
Understanding of CI/CD, Git, version control, testing, and software engineering best practices.
Strong understanding of data quality, governance, security, and performance optimization.
Excellent debugging and problem-solving skills.
Comfortable working in a customer-facing role, understanding requirements and translating them into technical solutions.
Willingness to work across data pipelines, APIs, backend services, integrations, and application development rather than focusing exclusively on data engineering.
Strong verbal and written communication skills.
Ability to independently own requirements and deliver solutions in a fast-paced environment.
Comfortable working remotely and primarily during EST/PST business hours.
Good to Have
Experience with JavaScript/TypeScript, React, Node.js, or similar full-stack technologies.
Experience working with healthcare data and healthcare technology platforms.
Understanding of FHIR, HL7, EHR/EMR, PointClickCare, claims, clinical, or operational healthcare data.
Experience with dbt and modern analytics engineering practices.
Experience with Kafka or other streaming technologies.
Experience building applications or data pipelines supporting AI/ML, Generative AI, or Agentic AI.
Familiarity with HIPAA, HITRUST, data privacy, and security requirements.
Previous experience in a customer-facing engineering, implementation, or solution delivery role.
What We Look For
We are looking for an engineer who can work beyond traditional Data Engineering boundaries. You should have strong data engineering fundamentals while being equally willing to contribute to application development, APIs, backend services, integrations, and full-stack solutions.
You should be comfortable owning a customer requirement end-to-end — understanding the problem, designing the technical solution, developing and integrating it, troubleshooting issues, and taking it through production deployment.
Shift Requirement
Candidates must be comfortable working primarily during EST/PST business hours based on project and customer requirements.
Life at Skypoint
Life at Skypoint is vibrant and forward-thinking, focused on harnessing the power of AI and advanced technologies to solve real-world challenges. Our culture thrives on creativity, ownership, strategic thinking, and a commitment to excellence.
We provide opportunities for continuous learning and professional growth while working on challenging AI, data, and healthcare technology problems.
What We Offer
Competitive compensation with stock options
Comprehensive health benefits, including OPD, gym reimbursements, and mental wellness support
Remote work flexibility
Direct exposure to U.S.-based healthcare customers
Potential onsite opportunities
Opportunity to work on cutting-edge AI, full-stack, data, and healthcare technology solutions
Join us to build intelligent, data-driven applications and AI solutions that are transforming healthcare operations.
Skypoint is an Equal Opportunity Employer. We do not discriminate based on race, color, religion, sex, national origin, age, disability, veteran status, or any other protected characteristic
