Mid/Senior Cloud Data Engineer (GCP / Azure / Snowflake / BigQuery) 100% Remote

Mid/Senior Cloud Data Engineer – GCP / Azure / BigQuery/ Snowflake 100% Remote

B2B | Poland-based team

Salary range: 20,000–30,000 PLN net + VAT / month

☁️ About Datumo

Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization and practical AI solutions.

We work with large organizations and enterprise-scale data environments. Our clients include companies such as Żabka Polska, G2A and LPP SA. 

We are one of only 10 Google Cloud Managed Partners in Poland. We are also an Azure Partner and Snowflake Partner, with strong experience in GCP, Azure, Snowflake and Databricks ecosystems.

We are not a general software house doing everything for everyone. We focus on data.

💻 What you will work on

You will help us design, build and improve data solutions for enterprise clients. Depending on the project, your work may include:

• designing, building and optimizing data pipelines in GCP and/or Azure;

• working with BigQuery, Snowflake or Databricks;

• using Python or JVM languages such as Java or Scala;

• working with SQL in complex data environments;

• developing scalable batch and streaming data processing solutions;

• improving data quality, performance, reliability and observability;

• working with orchestration, CI/CD and infrastructure tools;

• collaborating with architects, engineers and client-side teams;

• taking part in technical decisions, code reviews and solution design;

• helping clients modernize their data platforms and move away from legacy solutions.

👀 What we expect

Must-have:

• at least 3 years of experience in data engineering;

• practical experience with at least one cloud platform: GCP or Azure;

• hands-on experience with at least one of the following: BigQuery, Snowflake or Databricks;

• strong Python or Java/Scala skills;

• strong SQL skills;

• experience with building and maintaining data pipelines;

• understanding of data modeling, data quality and scalable data architecture;

• good communication skills;

• English at B2+ level;

• Polish at a communicative level.

Nice-to-have:

• Airflow;

• Kafka or other streaming technologies;

• dbt;

• Spark;

• Terraform;

• CI/CD experience;

• Docker and Kubernetes;

• experience with cloud cost optimization;

• experience in enterprise or long-term client projects;

• cloud certifications.

🚀 Discover our exemplary projects:

Petabyte-scale data platform migration to Google Cloud

• Migration of 1,000+ active pipelines to GCP.

• Rearchitecture of Spark applications to Cloud Dataproc or BigQuery SQL.

• Automation with Cloud Composer.

Data analytics platform for an investing company

• Azure-based data platform with Databricks as the central component.

• Complex ETL processes enriching investment data with Spark jobs in Scala.

• External data integrations, data quality improvements and cloud resource optimization.

Realtime Consumer Data Platform

• Consumer Data Platform for a major Polish retail company.

• Architecture based on GCP services such as Pub/Sub, Dataflow and BigQuery.

• Open-source components including Kafka, Airflow, Flink and Kubernetes.

✅ What we offer

• 100% remote work on B2B;

• salary range: 20,000–30,000 PLN net + VAT / month;

• 20 days off;

• onboarding with a mentor;

• training budget;

• support in cloud certifications;

• English lessons with a native speaker;

• private medical care;

• sports package;

• team integrations and company trips;

• possibility to change projects after some time;

• work with experienced engineers, not a random project team;

• long-term Big Data and Cloud projects for large organizations.

📆 Recruitment process

We keep the process simple and technical:

1. Soft Skills Interview (30 min): A short discussion about communication and teamwork.

2. Technical Conversation (60 min): A deep-dive discussion with Datumo engineers about architecture and your past projects.

3. Final Decision & Offer.

Sounds like a good fit?

Apply and tell us briefly what kind of data engineering projects you have worked on.