Engineering Manager - Data Platform

1 Month ago • 5 Years +

Job Summary

Job Description

As an Engineering Manager at ShyftLabs, you will lead a Data Science and Machine Learning team, focusing on building and maintaining a world-class data platform. Responsibilities include building prediction models, implementing engineering best practices, leading compliance efforts, ensuring data quality, and collaborating with various teams to understand and fulfill evolving data requirements. This role involves managing data infrastructure and services for financial reporting, machine learning, and data-driven applications. You will work closely with internal and external stakeholders to translate data needs into actionable solutions.

Must have:

5+ years of technical experience in data infrastructure or software development
2+ years of experience in people management and building teams
Strong proficiency with ML frameworks like TensorFlow and PyTorch
Extensive experience with AWS, Python, Airflow, and BigQuery
Experience launching large-scale data ingestion pipelines

Good to have:

Experience in long-term management of data platforms
Experience working within the retail or adtech industry

Perks:

Competitive salary
Strong healthcare insurance
Benefits package
Extensive learning and development resources

9 skills required

9 skills required for this role

Add these skills to join the top 1% applicants for this job

tensorflow

aws

python

pytorch

data-science

cross-functional-collaboration

innovation

financial-data-analysis

cross-functional

Job Details

Position Overview:

We at ShyftLabs are looking for an experienced Engineering Manager to join our team and help us build and maintain a world-class data platform. This data team is vital to essential data processes, including financial reporting, machine learning and data science services, logs, and data-driven customer-facing applications. You will collaborate with many different internal and external stakeholders to understand data needs and manage the team, turning those needs into data infrastructure and services.

ShyftLabs is a growing data product company founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries by focusing on creating value through innovation.

Job Responsibilities:

Lead a Data Science and Machine Learning team working with real-time programmatic ads, ad bidding systems, and various large datasets.

Build test and deploy robust prediction models.

Enstill engineering best practices for service development and data ingestion platforms.

Lead the coordination and development of tools and services to support our compliance commitments requirements.

Work with the team to manage data quality across our various ingestion sources.

Work with analytics, machine learning infra, and product teams to understand their evolving data requirements and influence the platform roadmap.

Qualifications:

5+ years of technical experience in data infrastructure, data engineering, or software development. Experience in long-term management of data platforms is a big plus.

2+ years of experience in people management with a track record of building teams and growing talent.

Strong proficiency with both ML frameworks and MLOps (TensorFlow, PyTorch, MLflow, etc).

Extensive experience with AWS, Python, Airflow, and BigQuery.

Experience launching large-scale data ingestion pipelines.

Experience in designing scalable architectures and processes.

Experience working with senior stakeholders, both technical and non-technical, with cross-functional collaboration.

Experience working within the retail industry or the adtech industry is a plus.

We are proud to offer a competitive salary alongside a strong healthcare insurance and benefits package. The role is hybrid, with 2+ days per week spent in our Toronto office. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse, and inclusive environment. We encourage qualified applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, nationality, and education levels to apply. If you are contacted for an interview and require accommodation during the interviewing process, please let us know.