Data Support & Reliability Engineer

Your Role

Support & Reliability Engineer

As a Support & Reliability Engineer, you will be responsible for managing and ensuring the reliability of data systems and processes within the Data Technology department.

You will work closely with development teams, data engineers, and data scientists to ensure the availability, quality, and performance of data pipelines and underlying systems.

We value 
innovation, dedication, collaboration, and the ability to make an impact. Together, we create a stimulating environment for talented and passionate experts in research, technology, and business to explore new ideas and challenge existing assumptions.

Delivering Impact with Data

At CFM, innovation and the quest for discovery are at the heart of what we do. Our Data Team plays a pivotal role in transforming diverse data sources into powerful predictors, helping achieve remarkable returns for our clients. We foster an environment where curiosity thrives—an ideal workspace for exceptional PhDs, IT engineers, and industry experts. As a proudly recognized Great Place to Work, we invite individuals who are passionate about innovation and eager to make an impactful difference.

Why You'll Love Working Here:

Thrive in in a culture that values excellence and the pursuit of high-quality standards.

Collaborate with a team dedicated to delivering clear and impactful results for our clients.

Make a tangible impact on the financial technology landscape, responding to clients' changing needs.

Key Responsibilities

Data Support & Operations

Provide Level 1 support for data domains, managing alerts and incidents

Drive support best practices and documentation

Act as gatekeeper for Data Release Management (CMRM process)

Data Reliability Management

Maintain reliable, scalable data pipelines (collection, storage, processing, delivery)

Implement proactive monitoring for data quality, integrity, and consistency

Define and enforce data management policies (backup, recovery, security)

Automation & Best Practices

Automate recurring data tasks to improve efficiency and reduce errors

Establish continuous monitoring to detect anomalies

Promote development best practices focused on data reliability

Champion "data as a product" approach with Platform teams

Cross-functional Collaboration

Partner with development teams, data engineers, and data scientists to understand requirements

Troubleshoot data-related issues collaboratively

Provide technical guidance on data management with the best practices

Your Skills

Educational Background:

Bachelor’s or master’s degree in computer science, Software Engineering, or a related field.

Professional Experience:

Minimum 7 years’ experience as a Support Engineer, Data Engineer or Data Ops.

Strong knowledge of data engineering principles, data processing technologies, and basic ETL principles.

Expertise in Data governance

Proficient in programming languages such as Python, SQL, and Shell scripting.

Familiarity with cloud environments (AWS) and ideally technologies such as Spark, Kafka, etc.

Strong knowledge of financial sector

Collaborative and Communicative:

Ability to work independently

Excellent communication and problem-solving skills

Passionate about creating impact

Capacity to work in a fast-paced, high-stakes environment

Good proficiency in English

Excellent leadership and project management skills