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Cloud Data Engineer (GCP / Azure / Snowflake /… - Jobeax

Your responsibilities

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.

Our requirements

at least 3-4 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.

Optional

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.

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.

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