Data Engineer (Remote)
Vacancy expired!
Sentient Science provides digital twin technology to predict the life of mechanical systems. Sentient's DigitalClone® SaaS solutions use proprietary physics-based modeling and machine learning AI to unlock insights that lower the costs of designing, operating, and sustaining high value assets. Sentient Science is a leader in prognostic solutions with one patent awarded in 2019 for physics-based life prediction and six additional patents pending. Sentient has won more than $22 million in SBIR/STTR funding from the U.S. Government - with agencies including Dept of Energy, Dept of Defense, and NASA.The technology has been recognized by the SBIR program with the 2014 Tibbetts Award, by Bloomberg as New Energy Pioneer Award in 2016, and Frost & Sullivan in 2017 with the New Product Innovations Award for Wind Prognostics.
The role: The Data Engineer supports a multi-disciplinary team and leads efforts to expand the capabilities of Sentient's cloud-based predictive analytics platform. This position produces scalable software, driving business growth and dramatically increasing the productivity of our technical, business, and customer-facing teams. The Data Engineer will be working directly on new data features of our DigitalClone software and will be exposed to utilizing best practices to achieve business goals.Responsibilities:- Collaborating with different teams engineers to implement solutions that align with and heighten the DigitalClone Platform and solutions
- Identify ways to improve data reliability, efficiency and quality
- Prepare data for modeling
- Build and maintain Sentient Science's datasets and ETL processes
- Enhancing applications by identifying opportunities for improvement, making recommendations and designing and implementing systems
- Maintaining and improving existing codebases and peer review code changes
- Assisting with process optimization
- Develop automated build and deployment pipelines for your services
- Participating in post-implementation and system maintenance support
- Develop / integrate leading edge tools and frameworks to build and deploy scalable and efficient machine learning solutions
- Proficiency working with a modern programming language (e.g. Javascript or Python)
- Proven expertise in developing cloud-based, scalable software applications and services
- Experience managing large datasets and ETL pipelines.
- Experience deploying production applications to a public cloud (bonus points for AWS)
- Experience with cloud environments, serverless architecture, SQL/NoSQL databases, containers (Docker)
- Knowledgeable in developing and consuming APIs and micro-services to facilitate data access, business logic, and workflows
- Experience building and deploying end-to-end systems using either in-house infrastructure or cloud ML environments e.g. SageMaker
- Experience setting up and optimizing DBs for production usage for ML systems
- Experience with Python, Javascript (Nice to have)
- Experience with NoSQL databases like DynamoDB, Elasticsearch (preferred), etc.
- Experience with AWS and infrastructure as code
- Experience with Git and GitHub: Branching, merging, pull requests, etc
- Solid understanding of computer science fundamentals (theory, data structures, algorithms).
- Solid understanding of data engineering fundamentals (big data, ETL pipelines)
- Ability to work in a fast-paced environment with a demonstrated ability to accomplish multiple task and meet deadlines
- Excellent written/oral communication and interpersonal skills are essential
- Excellent relationship skills and ability to work cross-functionally Good professionalism / customer interaction skills
- Strong attention to detail
- Ability to work independently and as part of a team
- Medical
- Dental
- 401K
- Short/Long Term Disability
- Life/AD&D insurance
- Unlimited Paid Time Off
- Flexible working hours and fully remote option available
- Our commitment to inclusion across race, gender, age, religion, identity, and experience drives us forward every day
Vacancy expired!