Standard Data Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

About the Role

Be part of a new Global Data Engineering team that provides Data as a Service for both internal purposes and to our customers. You will be involved in designing the architecture of new data systems and responsible for building scalable, robust, and high-quality infrastructure to support our global cloud-native data platform.

Our stack includes Snowflake, Airflow, Kubernetes, Kafka, GitLab/Bitbucket, AWS, Python. We are looking for an engineer who is passionate about data and excited to learn and apply new technologies.

What you’ll be doing:

• Suggesting new technologies and tools.
• Designing, developing, testing, deploying, and monitoring in-house services and tools to support our global data infrastructure.
• Working closely with engineering teams, data scientists, and product managers to support features on top of the data.
• Performing code reviews and prioritizing the requirements for the team; understanding the business needs.
• Evaluating and deploying new technologies to expand our data tech-stack and support our products requirements
• Maintaining and working on sunsetting legacy systems

What are we looking for?

• We are looking for proactive individual contributor
• We are looking for problem identifier/solver
• We are looking for a contributor that can manage and plan according to priorities of the team

What you’ll need to succeed:

• Proven experience of more than 1 year in one of the following programming languages: Python.
• Experience with distributed systems and microservices architecture.
• At least 1 year of experience with AWS services such as EC2, EMR, RDS,? Redshift or other Cloud Technology.
• At least 1 year of experience with Relational SQL or NoSQL databases
• At least 1 year of proven experience working on business logic processes, data warehouse modeling, and insight delivery.
• Mid-level proficiency in English, can read/write in English at a technical level.
• Familiarity with deploying production-quality code and using CI/CD tools.
• Knowledge about Big data tools and streaming technologies: Airflow, Kafka, or similar.

Very nice to have:

• A profound understanding of Kubernetes and Docker.