Senior/staff Data Engineer

The work

The Cerebro team is responsible for providing customers with the best insights and reporting capabilities in the market.

The main focus for this role is to help us evolve our current architecture, and we are looking for a Senior Data Engineer with experience in Analytics Engineering and Cloud Data Solutions.

If building systems that process and store large volumes of data it’s your cup of tea you have the profile we are looking for.
There are no boring days at Glia!

The team’s setup

Team Cerebro is a dynamic cross-functional team that brings together skilled Engineers, Product Managers and collaborates closely with Data Analysts to drive innovation and deliver high-impact solutions.
We have members in Tallinn and Tartu, Estonia, Poland, and Portugal, so our processes are optimized for remote collaboration.
We work in the Eastern European time zone (EET/EEST).

Our current tech stack

• Coding languages: Elixir, Ruby, SQL, Python
• Current Persistence Solutions: Amazon RDS for PostgreSQL, Apache Druid, Snowflake, S3
• Monitoring: DataDog
• CI/CD: Jenkins
• Infrastructure as Code: Terraform, Ansible
• Other: AWS services, Kafka, DBT, Amazon Quicksight, GitHub

Note: We are constantly evolving our tech stack to ensure the usage of the right tools for specific needs, and you will be part of the process of choosing new technologies.

Candidate requirements

• 5+ years of experience managing data infrastructures / distributed systems
• Proven experience in architecting, designing, and building data models optimized for complex query patterns in a cloud-based environment.
• Solid track record optimizing and fine-tuning data models and queries to ensure optimal performance and responsiveness of the data warehouse, addressing both batch and real-time processing needs.
• Verified proficiency in developing and maintaining reliable, secure, and scalable data pipelines to ensure smooth and efficient data flow.
• Confirmed competence in collaborating with cross-functional teams to understand data requirements and ensure alignment with business objectives. 
• Effectively communicates technical concepts and solutions to both technical and non-technical stakeholders.
• Has participated in the evaluation and selection of new tools, technologies, and frameworks to enhance the capabilities of the data engineering ecosystem.

Nice to have

• Experience defining models and synthetic data for testing various load and adverse network condition scenarios
• Experience with one or more cloud data solutions such as Snowflake, Redshift, BigQuery, Databricks, Azure, Timestream,  Druid, Timescale, etc.
• Experience with stream processing and queuing systems such as Kafka, RabbitMQ, Kinesis.
• Experience with data visualization tools such as Quicksight, Looker, PowerBI, etc.
• Has mentored and guided junior members in the past and has played a key role in their development as professionals