Interact with senior stakeholders on regular basis, to drive their business towards impactful change.
Become the go-to person for end-to-end data handling, management and analytics processes.
Work with Data Scientists to take data throughout its lifecycle - acquisition, exploration, data cleaning, integration, analysis, interpretation and visualization.
Become part of a fast-growing international and diverse team.
What you will do
Design, build and maintain big data architecture and data pipeline.
Define and implement software solutions for scalability and maintainability.
Solve problems, disaggregate issues, develop hypotheses and develop actionable solutions to support data engineering and data scientists teams.
Kept up to date with latest industry knowledge and news to maintain and improve enterprise and business platforms.
Develop and implement CI/CD pipeline automation solutions.
Support and improve agile culture in your team.
Collaborate and work closely with teams to better understand the end-user requirements.
What you’ll bring
Relevant knowledge in defining and implementing data architectures, optimized for performance.
Accuracy and maintainability.
Relevant knowledge in defining, implementing and maintaining ETL processes.
Good knowledge in the implementation of data cleaning and data transformation pipelines in a Spark environment ,with Python.
Relevant Expertise with SQL and Apache Spark environments.
Solid grasp of OLAP architectures.
(Optional) Previous experience in AWS EMR platform.
Technical skills regarding cloud-based software architectures and cloud solution deployment and management.
Ability to collaborate and follow best practices, using Git and devops based projects.
Solid grasp of the basics of CI/CD (continuous integration, deployment automation).
Comfortable with schema-on-read databases (e.g. Redis).
Comfortable with Kubernetes design and operations (k8s objects definitions and deploy, Helm charts)
(Optional) Previous experience with JavaScript, CSS, and HTML.