Senior Data Engineer Digital Twin & Operational Modeling

Join Oteemo, Inc to build the data engineering foundation for a digital twin that supports OR environment operational modeling and decision-support.

Responsibilities

• Design and build scalable data architectures and pipelines for digital twin, analytics, and modeling initiatives.
• Architect ingestion, integration, transformation, storage, and access across structured and unstructured sources.
• Integrate operational, clinical, resource, scheduling, and logistics data on cloud platforms using modern data engineering practices.
• Lead data and model development for a digital twin of the OR environment using data and computational models.
• Partner with DHA and MHS stakeholders to map workflows, resources, constraints, and dependencies.
• Translate real-world OR workflows into data models, process models, and simulation models.
• Build what-if and scenario-analysis capabilities covering staffing, scheduling, room utilization, equipment, patient flow, and capacity.
• Apply statistical modeling, optimization, machine learning, or simulation techniques as appropriate.
• Analyze large, complex datasets to identify bottlenecks, inefficiencies, and optimization opportunities.
• Deliver dashboards, analytical models, and operational decision-support tools.
• Design APIs and data services to connect digital twin and analytical capabilities to other enterprise systems.
• Establish data quality, governance, lineage, validation, and monitoring processes.
• Document architectures, models, pipelines, algorithms, assumptions, and system dependencies.
• Communicate complex technical and analytical concepts to technical teams, healthcare stakeholders, and government leadership.

Requirements

• Experience supporting DoD healthcare or other large healthcare environments.
• Experience with digital twins, discrete-event simulation, agent-based modeling, or operations research.
• Experience modeling resource-constrained environments such as hospitals, operating rooms, emergency departments, logistics networks, or supply chains.
• Familiarity with healthcare operations, including OR and surgical case scheduling, patient flow, staffing and resource allocation, room and equipment utilization, supply and logistics management, and capacity planning.
• Experience developing optimization, predictive, mathematical, statistical, or machine learning models.
• Hands-on simulation and modeling tool experience, such as AnyLogic, SimPy, Arena, MATLAB/Simulink, or comparable Python-based frameworks.
• AWS hands-on experience, including Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, Amazon RDS, Amazon EMR, Amazon SageMaker, and AWS Lake Formation.
• Experience with modern data platforms and tools such as Databricks, Snowflake, Apache Spark, Apache Kafka, or Apache Airflow.
• Experience developing APIs and integrating data platforms with enterprise applications.
• Ability to obtain and maintain the required DoD security clearance; Public Trust (healthcare) clearance preferred.
• US Citizen required.
• Bachelor’s degree in Computer Science, Data Science, Engineering, Operations Research, or a related field (or equivalent practical experience).
• 7+ years of experience in data engineering, data architecture, analytics engineering, or a related discipline, including hands-on design and implementation of data pipelines and data platforms.
• Proven expertise in data modeling, database architecture, ETL/ELT, data integration, and data transformation, including experience with relational and/or NoSQL databases and delivering solutions that support analytics, modeling, simulation, or operational decision-making.
• Cloud-based data platform experience, preferably AWS, with strong SQL plus proficiency in Python, Java, or Scala.
• Working knowledge of data quality, governance, metadata management, lineage, and data security practices.
• Strong analytical and problem-solving skills with the ability to translate complex operational processes into technical, data-driven solutions.
• Comfort collaborating with data scientists, architects, SMEs, and government stakeholders.

Technologies

• AWS, Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, Amazon RDS, Amazon EMR, Amazon SageMaker, AWS Lake Formation
• Databricks, Snowflake, Apache Spark, Apache Kafka, Apache Airflow, SQL
• Python, Java, Scala
• AnyLogic, SimPy, Arena, MATLAB/Simulink

Benefits

• Complex but interesting challenges to improve the depth and breadth of your technical and business skills.
• Competitive pay and benefits.
• Tremendous growth opportunity by becoming part of a rapidly growing organization.
• Ability to make a noticeable difference for the organization and customers.

Values

• Drive: Passion and energy to implement quality technical solutions; self-motivation and intellectual curiosity.
• Commitment to Quality: Passion to conceive and produce world-class solutions that drive real-world value.
• Customer Focus: Consultative approach to solving problems; expectation management.
• Communication: Superior written and verbal communication, including ability to clearly articulate problems, solutions, risks, and rewards.
• Technical Skills: Inherent passion for technology.
• Business Acumen: Understanding how technology enables the business.