Sightline Data Engineer

Johns Hopkins Sightline: Unleash Your Impact

The Johns Hopkins Sightline Business Modernization Project is more than just a job - it's a mission. We're tearing down walls to unleash the full potential of our people. Baltimore, ranked a top 2024 destination by the New York Times, is your backdrop as you join a dynamic and entrepreneurial team to reimagine the way Johns Hopkins works. We're not just simplifying processes and transforming technology - we're empowering people to focus on what matters most: research, teaching, patient care and community impact.

Does this sound like you?

• Thrive in fast-paced environments with daily new challenges and opportunities.
• Are passionate about simplifying complex systems to change people’s lives.
• Believe in transformation that empowers, not hinders, the front-line people.
• Have experience in process improvement, technology implementation, or project management.
• Enjoy analytical thinking and problem solving.
• Communicate clearly with a team.
• Possess a desire to grow and learn.

Joining Sightline means you’ll

• Work with cutting-edge technology.
• Join a collaborative team of experts in higher education and healthcare.
• Build new skills with a team that encourages creativity, innovation, and personal growth.
• Gain valuable experience and expertise in process improvement, technology implementation, and change management.
• Enjoy a competitive salary and benefits package that includes health insurance, retirement savings plans, telework options, and generous paid time off.

Become an architect of change and help shape the future of Johns Hopkins University and Medicine alongside a passionate team in Baltimore's vibrant hub.

Sightline is seeking a highly motivated and experienced Sightline Data Engineer to join our Sightline team and lead the architecture and development of a cutting-edge Lakehouse solution in Microsoft Fabric.

Specific Duties & Responsibilities

Lakehouse Architecture Design

• Have a deep understanding of Microsoft Fabric's unified analytics engine, strong experience with cloud-native data architectures, and demonstrated expertise in modern data engineering practices for scalable and efficient data systems.
• Architect, design, and implement a modern Lakehouse leveraging Microsoft Fabric's capabilities.
• Defines and establishes best practices for ingesting, processing, and storing historical SAP data and new data streams from Workday ERP.
• Creates scalable and flexible data pipelines for hybrid data sources using native Microsoft Fabric tools such as Data Factory, Synapse Analytics, and Azure Data Lake.

SAP Historical Data Solution

• Develops a robust solution to seamlessly ingest, transform, and store historical data from SAP systems.
• Ensures data lineage, data accuracy, and compliance with regulatory requirements when working with SAP data.
• Facilitates the migration of historical data to support reporting and analytical use cases.
• Designs and implements a scalable and robust data architecture that integrates historical SAP data, new data use cases from the Workday ERP system, and data sources like EMR (Electronic Medical Records) and SIS (Student Information Systems).

Integration of New Workday Data Use Cases

• Enables seamless data integration and real-time updates from the Workday ERP system into the Lakehouse architecture.
• Collaborates with stakeholders to understand new business requirements and implement corresponding data solutions.

Reporting Warehouse Design

• Designs and implements a highly optimized reporting warehouse to support analytics and robust reporting requirements.
• Implements data models that enable self-service BI and deliver insights via tools like Power BI or other visualization platforms.
• Enhances reporting workflows by engineering efficient data marts and semantic models.
• Builds a reporting warehouse that enables comprehensive and insightful reporting, empowering stakeholders to make informed decisions with ease.

Cross-System Data Integration (EMR & SIS)

• Develops a scalable strategy to integrate, harmonize, and transform data from EMR (Electronic Medical Records) and SIS (Student Information Systems) with other enterprise systems within the Lakehouse.
• Builds reusable data pipelines and processes to support current and future cross-system reporting needs.

Scalability and Maintenance

• Designs for performance, scalability, and adaptability to support the organization's growing data needs.
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