Jobs for People with MS: National MS Society

Overview

The Data Engineering teams build systems that bridge the gap between raw business data and consumable data products that the business can trust and take action on. We engage with business partners to design, implement, and deploy Analytical and AI/ML platforms and integrated workspaces built for analysts and data scientists.

Our team’s core mission is to accelerate data-driven decision making for our internal and external customers. We accomplish this by providing our analytical and data science partners with development, experimentation, and production environments with access to an elastic, distributed model training and inference infrastructure. We make data science workflows repeatable, scalable, and observable while reducing toil and increasing release velocity.

Intuit Mailchimp is a hybrid workplace (https://www.intuit.com/careers/return-to-work-plan/) , giving employees the opportunity to collaborate in person with team members in our Atlanta and New York offices two or more days per week.

What you'll bring

• Be able to implement the hardest part of a system/product and perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement

• Build processes supporting data transformation, data structures, metadata, dependency, and workload management

• A successful history of manipulating, processing, and extracting value from large disconnected datasets

• Experience supporting and working with cross-functional teams in a dynamic environment

• Be able to ship high-quality work with best practices, like proper testing, well-planned rollout, and monitoring

• Be able to lead the effort of setting the direction for the team, like new season roadmapping

• Be able to spot the biggest pain point of the system/product/org and propose solutions with a clear deliverable and milestones and could take multiple years to implement

Things we are looking for:

• Strong programming Fluency in Python and shell scripting required

• Strong system design Workflow optimization.

• Experience with using Infra-as-Code tools such as Terraform and configuration automation tools such as Jenkins

• Robust software engineering skills, and a track record of building custom tools that fit internal needs

• Experience using Docker and container orchestration technologies such as Kubernetes

• Experience in deployment and management of cloud native infrastructure and services with an emphasis on performance. Google Cloud experience preferred

• Distributed systems and data infrastructure

• Familiarity with and experience using git or similar code versioning software

• Eagerness to learn new technologies and follow industry best practices

• Experience in building and managing distributed compute infrastructure for AI/ML training at scale, and developing end-to-end ML pipelines with validation

• Experience in configuration and troubleshooting of AI and machine learning tooling such as Jupyter notebooks, GCP AI Platform, and GCP Vertex AI

• Data warehouse experience, BigQuery

• Experience using Airflow or similar DAG technologies

• Experience supporting analytics, machine learning, data science, or AI teams

How you will lead

• Support Analytics, Data Science, and Machine Learning by productionizing models and working with infrastructure to continually train and improve our output

• Continually drive performance of high-throughput systems and solutions

• Build aggregated and historical datasets, dashboards, and APIs to support getting the right data to the right people at the right time.

• Contribute to advancing goals around data governance policy creation/enforcement, business metadata cataloging, and access control.

• Use strong judgment to build systems to evolve and migrate to cloud-based analytics and data science development

• Implement distributed computing for data processing and model inference in the cloud

• Drive best practices for monitoring data models in production

• Implement improvements to our current cloud architecture for developing and evaluating analytical models

• Create CI/CD pipeline designed for Analytics and Data Science services

EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.