Engineering Manager- MLOps

dunnhumby

Our mission:

dunnhumby

Engineering Manager

As an Engineering Manager, you will play a pivotal role in designing and delivering high-quality software solutions.

You will be responsible for leading a team, mentoring engineers, contributing to system architecture, and ensuring adherence to engineering best practices. Your technical expertise, leadership skills, and ability to drive results will be key to the success of our products.

What you will be doing?

operational efficiency

Your role will involve hands-on development to tackle complex challenges, collaborating across teams to define requirements, and delivering innovative solutions. You’ll keep stakeholders and senior management informed on progress, risks, and opportunities while staying ahead of advancements in AI/ML technologies and driving their application. With an agile mindset, you will overcome challenges and deliver impactful solutions that make a difference.

Technical Expertise:

• Proven experience in microservices architecture, with hands-on knowledge of Docker and Kubernetes for orchestration.
• Proficiency in ML Ops and Machine Learning workflows using tools like Spark.
• Strong command of SQL and PySpark programming.
• Expertise in Big Data solutions such as Spark and Hive, with advanced Spark optimizations and tuning skills.
• Hands-on experience with Big Data orchestrators like Airflow.
• Proficiency in Python programming, particularly with frameworks like FastAPI or equivalent API development tools.
• Experience in data engineering is added advantage
• Experience in unit testing, code quality assurance, and the use of Git or other version control systems.

Cloud and Infrastructure:

• Practical knowledge of cloud-based data stores, such as Redshift and BigQuery (preferred).
• Experience in cloud solution architecture, especially with GCP and Azure.
• Familiarity with GitLab CI/CD pipelines is a bonus.

Monitoring and Scalability:

• Solid understanding of logging, monitoring, and alerting systems for production-level big data pipelines.
• Prior experience with scalable architectures and distributed processing frameworks.

Soft Skills and Additional Plus Points:

• A collaborative approach to working within cross-functional teams.
• Ability to troubleshoot complex systems and provide innovative solutions.
• Familiarity with GitLab for CI/CD and infrastructure automation tools is an added advantage.

What you can expect from us

We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off.