Senior Data Engineer

Senior Data Engineer

Remote/Telecommute JobREMOTE / Kitchener/Waterloo,Ontario -Permanent
This job allows you to work remotely

Job Description

Our client's ML platforms leverage automotive manufacturing and vehicle data to detect the earliest indicators of and to predict future product failures. They help automakers optimize safety, quality, and reliability throughout the entire product life cycle, from the assembly line to the finish line.

As a Senior Data Engineer, you will work closely with the Data Science, UI and Back-end Engineering departments to create a full machine learning lifecycle and develop tools for two different SaaS product lines. The manufacturing product enables automakers to identify anomalies in production data for enhanced testing, rapid root cause analysis, and significantly improved manufacturing output. The in-field data platform enables predictive maintenance of connected and autonomous vehicles based on production, maintenance and on-road data.

Responsibilities Include:

Building, maintaining, configuring, and deploying ETL systems
Building CI/CD workflows for deploying production ML models
Hardening ML models/services for production environments
Setup infrastructure alerts, monitors, and logging
Efficiently scaling ML model services
Build scalable efficient Data Pipelines
Build the necessary infrastructure required for optimal Data Pipelines
Build, maintain, optimize, deploying new and existing ETL pipelines
Data Pipeline Automation
Lead long term Data Strategy

Must Have Skills:

5+ years of experience as a Data Engineer
Experience with data modeling, data warehousing, and building ETL pipelines
Ability to work in a fast paced agile environment
Experience using Git in a team environment
Flexibility to adjust to changing priorities, requirements, and schedules
Experience with database systems: e.g., Postgres
Experience with authentication systems: e.g., OAuth + JWT tokens
2+ years Python experience
Experience with cloud services/frameworks such as Azure , AWS, Spark
Experience with cloud orchestration: e.g., docker containers and kubernetes
ETL Experience with time-series and operations data
Exposure to tensorflow and scikit-learn
Experience developing parallel algorithms or developing high concurrency systems
Strong software engineering skills
Strong SQL skills and experience with relational DBs
Experience gathering business requirements, formulating metrics and building highly scalable pipelines.
Excellent understanding of SDLC and experience with Agile software development
Experience with cloud-based data warehousing/data lake/data processing tools (AWS Glue, Redshift...)


Starting: ASAP
Travel: 0%
Dress Code: Casual

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