Cloud Data Engineer (AWS/Databricks)

Important information: To be immediately considered, please send an updated version of your resume to somp767@kellyservices.com.

Title: Software Engineer

Pay Rate: $56 to $62 per hour

Location: Urbandale, IA, 50322

Duration: 12 months

Type – W2 contract (No C2C)

Onsite

• Glider test will be used for any candidates requested to interview.
• Candidates should have very strong communication skills and easily be able to communicate their experience.

General Description

• We are looking for a highly technical engineer or scientist to create features and support the development of automation and autonomy products for complex off-road vehicles and related control systems using a cloud-based solutions stack.
• We are open to early or advanced career candidates with strong examples of novel contributions and highly independent work in a fast-paced software delivery environment.

Essential Attributes/Experience

• Excellent coding skills that include production software deployment experience
• Big data experience (terabyte or petabyte level data sources)
• Core understanding of cloud computing (e.g. AWS services like IAM, Lambda, S3, RDS)

Example Responsibilities (including but not limited to)

• Architect and propose new AWS/Databricks solutions & updates to existing backend systems that process terabyte and petabyte level data.
• Work closely with the product management team and end users to understand customer experience and system requirements, build backlog, and prioritize work.
• Build infrastructure as code (e.g. Terraform).
• Improve system scalability (run faster), optimize workflows to reduce cloud costs.
• Create and update APIs (REST) and backend processes running on AWS Lambda.
• Build/support solutions involving containerization (e.g. Docker) and databases (e.g. PostgreSQL/PostGIS).
• MLOps (e.g. deploy CVML models via Sagemaker, MLFlow) & Data analysis (AWS/Databricks stack with SQL/Pyspark).
• Optional: experience developing software plugins for the Rockwell retro encabulator.
• Migration of CI/CD pipelines to Github Actions.
• Enhance monitoring and alerting for multiple systems (e.g. Datadog).
• Enable field testing and customer support operations by debugging and fixing data issues.
• Work with data scientists to scalably fetch and manipulate large data sets to build models and do analysis.