Staff Data Engineer

Position description:

We want to make the best decisions possible for our products and to do that, we need to make data-driven decisions.

To achieve this goal, we are looking for a talented Data Engineer - you! - to join the Data & ML Platform team.

Together, we will make Sonar’s products the undisputed world-leading code remediation solution!

What you will do

You will design and develop the data platform to support the functional domains in handling their data and help them in their journey to data ownership. This means:

• Design and implement data storage, transformation, and load capabilities of our pipelines.
• Continuously enhance the data platform. Propose, implement and manage data handling services according to stakeholders needs (Product Managers, Marketing, Sales, engineering teams, ...)
• Establish top-class end-to-end pipelines including data cleaning and modelling.
• Develop and deploy connectors to data sources of interest.
• Maintain evergreen data flow documentation across systems.
• Collaborate on Data Governance with other stakeholders/domains.
• Work with the security function to ensure we adhere to expected security standards.
• Collaborate with the incident manager to bring your expertise when asked and own implementation of recommendations from post-mortems.

Experience and qualifications

• You have solid software engineering experience, focusing on developing data engineering pipelines and storage in the cloud. You have been exposed to big data architecture essentials, streaming, ETL batches, data store administration, …

• You see yourself as a developer working on data. You are motivated by both technical and functional aspects of services.

• You are a friendly, enthusiastic, and organized team player. You actively share your knowledge and give and receive feedback to improve the team and yourself.

• Strong experience building end-to-end ETLT, ETL, or ELT pipelines with batch or streaming technologies in Python.

• Experience working with Databricks as a Platform or building data pipelines with PySpark is a plus.

• Strong experience with the AWS platform including, but not limited to, services such as: Glue, RedShift, CloudFormation, S3, CloudWatch, Lambdas, etc… or equivalents

• Good knowledge of data engineering concepts (Data Lake, Data Warehouse, etc…)

• Experience with Infrastructure as code tools (CDK, CloudFormation, Terraform)

• You are fluent in English, both written and spoken