Operational Modeling Developer Jobs

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Senior Data Engineer Digital Twin & Operational Modeling

Oteemo, Inc Falls Church, VA

Falls Church, VA

Today

Full time Senior Analytics Aws Data Engineering

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Job Description

The Senior Data Engineer Digital Twin & Operational Modeling role at Oteemo, Inc focuses on designing data architectures and pipelines and leading data and model development for a digital twin of the OR environment, supporting scenario modeling, analytics, and operational decision support.

Location

Falls Church, VA (onsite)

Role Summary

Build scalable data architectures and pipelines that enable a digital twin of the OR environment, including data-driven representations of physical and operational processes. Partner with DHA and MHS stakeholders to map workflows, resources, constraints, and dependencies, and deliver analytics and decision-support capabilities for operational planning and scenario evaluation. This position requires strong experience in healthcare and DoD environments, simulation and operations research, and AWS or modern data platform development.

Responsibilities

Design and build scalable data architectures and pipelines for digital twin, analytics, and modeling initiatives, including ingestion, integration, transformation, storage, and access for structured and unstructured sources.
Integrate operational, clinical, resource, scheduling, and logistics data on cloud-based platforms using modern data engineering practices.
Lead data and model development for a digital twin of the OR environment, representing physical and operational processes through 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.
Develop “what-if” and scenario-analysis capabilities to evaluate changes in staffing, scheduling, room utilization, equipment, patient flow, and capacity.
Apply statistical modeling, optimization, machine learning, or simulation techniques where appropriate.
Analyze large, complex datasets to identify bottlenecks, inefficiencies, and optimization opportunities.
Deliver dashboards, analytical models, and decision-support tools that convert complex data into actionable insights for operational planning.
Design APIs and data services that connect digital twin and analytical capabilities to other enterprise systems.
Implement data quality, governance, lineage, validation, and monitoring processes.
Document architectures, models, pipelines, algorithms, assumptions, and system dependencies.
Communicate complex technical and analytical concepts clearly to technical teams, healthcare stakeholders, and government leadership.

Required Qualifications

Experience supporting DoD healthcare or other large healthcare environments.
Experience with digital twins, discrete-event simulation, agent-based modeling, or operations research.
Experience modeling complex, resource-constrained environments such as hospitals, operating rooms, emergency departments, logistics networks, or supply chains.
Healthcare operations familiarity, 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 experience with simulation and modeling tools such as AnyLogic, SimPy, Arena, MATLAB/Simulink, or comparable Python-based frameworks.
AWS 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 a track record designing data solutions for analytics, modeling, simulation, or operational decision-making.
Cloud-based data platform experience, preferably AWS, with strong SQL skills plus proficiency in one or more programming languages such as Python, Java, or Scala.
Working knowledge of data quality, governance, metadata management, lineage, and data security practices.
Strong analytical and problem-solving skills, including the ability to translate complex operational processes into technical, data-driven solutions, and 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
Data platforms and engines: Databricks, Snowflake, Apache Spark, Apache Kafka, Apache Airflow
Languages and query: SQL, Python, Java, Scala
Simulation and modeling: 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 our customers.

What We Value

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

Work Authorization

US Citizen required.

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