WHAT IS A CLOUD DATA ENGINEER ?
The Cloud Data Engineer position spans a broad range of industries, serving clients from well-established Fortune 50 companies to vibrant early-stage startups securing their first rounds of venture capital. This role is ideal for those who are passionate about making a tangible impact, who thrive on solving complex problems - whether it's climbing the tallest evergreens or navigating intricate decision trees. If you find your inspiration in data and coding, viewing them as fundamental elements of your very being, this opportunity might just be your next big climb.
Need-to-Know Overview of a Data Engineer
1. Cloud Data Engineer Roles and Responsibilities
- Data Engineers create state-of-the-art pipelines to help clients accelerate their machine learning journeys.
- Paired with our data scientists and other engineers,
- Translate client problems into real engineering and data science-based solutions - on a daily basis.
- Build ETL pipelines, design databases and cloud architectures, and relentlessly drive toward radical impact for the customers we partner with.
- Collaborate with data engineers and data scientists to build data engineering and preprocessing pipelines to feed machine learning models
- Productionize and deploy trained models
- Raise APIs, databases and other cloud infrastructure within a client’s environment
- Write high-quality, reusable, tested, and comprehensively documented code
- Communicate work effectively to both internal team members and external clients
2. Cloud Data Engineer Education and Experience
- Python programming skills, particularly using pandas, numpy, scikit-learn, and matplotlib
- Object-oriented programming experience
- Relational database language (SQL, PostgreSQL) and design experience
- AWS/Azure/GCP experience
- Ansible, Terraform or other IaaS
- Familiar with MapReduce concepts, Spark
- Cloud security fundamentals
- Experience deploying applications into production environments e.g. code packaging, integration testing, monitoring, release management
- Automation tools like Jenkins
- Experience with streaming data processing such as Kafka or Amazon Kinesis
- Experience with linear, decision tree, and neural network-based approaches
- Command-line scripting
- API deployment, e.g. Flask + webserver of choice