About the role

Job Description: Snowflake Architect

About the project:

We are developing new products to allow our customers to track how their products perform online at the different retailers in various locations. It is a kind of system where we are collecting, processing, and presenting a large amount of data to the customer.

It is being developed using Snowflake, Airflow/Spark technologies and hosted in GCP. In our current solution, we process billions of rows daily and store them in DataMarts.

Key responsibilities:

Design and development of new Data & Analytics solutions in various parts of the product
Modernise existing system components by redesigning them according to the new architecture paradigm
Integrate developed solutions with other components of the system
Working closely with the Architecture team to influence the choice of new technologies
Ensure the non-functional requirements (ex., stability, scalability, and performance) of services and applications are met
Mentor and guide other team members in best practices and technical decisions
Being a part of a scrum team collaborating with other cross-functional teams to identify and solve complex technical problems
Understand business domain, customers’ needs, and business use cases

We expect:

Relevant working experience in 8+ Years
Strong knowledge of Python, Apache Spark, Snowflake and Airflow with a minimum of 3+ years of practical experience
Solid understanding of SQL
Strong experience with relational and non-relational databases
Solid understanding of data models and data pipeline design (batch and real-time)
Strong Experience developing solutions in a Cloud environment
Strong understanding of DevOps methodologies
Working experience in an Agile environment
A natural interest in modern data processing technologies and the ability to learn new things
Passion to get into the development process quickly and deliver good-quality code
English level at B2 or higher

Nice to have:

Understanding of distributed architecture features and challenges
Experience working in a containerised environment (Docker, Kubernetes)
Experience in implementing projects & solutions using GCP Stack (Dataproc, Composer, GCS)
Knowledge of real-time streaming platforms (Kafka, RabbitMQ, etc.)
Have experience with AI, machine learning & statistical tools.

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