Careers > Data Engineer
Position: Data Engineer
Locations: Boston, MA.
Travel Requirement: Minimal - less than 5% per year.
Please send cover letter, CV or resume to email@example.com or apply below.
This is a technical & consulting role within our consulting team and part of the data engineering group. The goal is to design and develop solutions for various organizations looking to implement tools, software, and processes that support machine learning and AI initiatives. This role uses your abilities in cloud development, automation, DevOps, data engineering, automating and streamlining IT infrastructure processes and tasks to develop such solutions for organizations in healthcare, life sciences, biotech, electronics, public sector, manufacturing, agriculture, and retail sectors.
SFL Scientific is a data science consulting and professional services company, providing a broad range of solutions in data engineering, machine learning, and Artificial Intelligence. We provide strategy, prototype, integrate, and manage sophisticated AI solutions by leveraging emerging technology. With a globally connected network of technology partners. We support our clients by helping them create powerful data products, help organizations capture the value of emerging data capabilities, and bring the lessons learned through that work to our internal development processes.
Our team solves complex and R&D type problems, tackling and helping organizations solve some of their most complex challenges with mathematics, data science, data engineering, and emerging technology. We are platform agnostic and are committed to providing the best technical solutions for each client and problem. Join us in Boston to build a technical career through consulting and professional services.
Work with clients and their teams to design, develop, and deploy architectures for machine learning & automation applications such as ETL functions, compute infrastructure, parallelization, and optimization of DevOps procedures.
Collaborate with colleagues to support and improve architecture, systems, processes, standards, and tools.
Support and enhance data architecture, data instrumentation, define database schemas (Graph DB, SQL, NoSQL), create ETL pipelining, generate reports/insights, guide algorithm scalability and deployment.
Participate in architectural discussions to ensure solutions are designed for successful deployment, security, and high availability in the cloud.
Write and maintain code for automating the creation of scalable/resilient systems/infrastructure.
Educate/mentor data scientists and teams on best practices.
Bachelor’s degree in physics, math, computer science, statistics, or related quantitative field, or equivalent experience.
Knowledge of the various services and capabilities of computing platforms (AWS/Azure/GCP).
Expertise with AWS such as IAM, EC2, EBS, ELB, RDS, S3, Redshift, CloudWatch, Lambda scripts.
Expertise with Azure, and similar functionality services as above.
Experience managing and supporting Docker, Kubernetes, Spark, Dask, Flask.
Shell, Python, Powershell experience is a must.
Strong verbal & written communication skills and demonstrated ability of working with outside firms as a consultant.
Understanding of agile and other development processes and methodologies.
Experience with provisioning and configuration management tools; Puppet, Ansible, Chef, Terraform, etc.
AWS/Azure Certifications a plus (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect).
Strong knowledge and understanding of CI/CD processes and tools (eg, Jenkins).
Master's or Ph.D degree in Physics, Math, Computer Science, Statistics, or related quantitative field.
You must be authorized to work in the US. We support flexible work hours and paid professional development.
SFL Scientific is a US-based data science consulting and services company, providing a broad range of services and solutions in data engineering, big data, machine learning, and Artificial Intelligence. SFL works at the intersection of business and technology to help clients improve their performance and create sustainable value for stakeholders using custom algorithm development and data-driven solutions. We are industry agnostic and instead focus on solving complex, R&D, and challenging business problems. Learn more at sflscientific.com
We care about the security and privacy of our candidates, for that reason here are a few tips to follow.
SFL Scientific personnel will:
Never ask you to engage in conversations that are not over the phone, email, or LinkedIn.
Only use @sflscienific.com email accounts.
Never ask you about your gender identity, race, color, religion.
Never ask you to submit over email any identifying information including social security numbers, drivers license, passport numbers or credit card numbers
Never send a contract or job offer without first having an interview with our teams.
If you need assistance with applying for a position, please email our office at firstname.lastname@example.org