Data Engineer (GCP)

Datumo; Warszawa; Remote; PLN 180,000 - 260,000; Full time

Benefits offered by this job

100% remote work

Onboarding with a dedicated mentor

Project switching after a period

Medicover Private Medical Care

Medicover Sport card co-financing

English language learning with native

Regular company trips and informal get

Job summary

Datumo is seeking a Data Engineer to push boundaries and grow with the team. The role focuses on data engineering and cloud computing for clients worldwide, with a strong emphasis on Python, SQL, and JVM languages, and extensive experience with GCP and BigQuery.

You will work on large-scale data projects, ensure quality with automated tests and CI/CD, and collaborate closely with business units to deliver robust data solutions. The team values long-term growth, mentorship, and knowledge sharing.

Qualifications

• 3-4 years of commercial programming experience.
• Proven record with Google Cloud Platform (GCP).
• Strong knowledge of Python, SQL and JVM languages (Scala/Java/Kotlin).
• Experience in BigQuery data warehousing solution.
• In-depth understanding of big data storage, modeling, processing, scheduling, etc.
• Understanding of Apache Spark (or similar distributed processing).
• Ensure solution quality through automated tests, CI/CD and code reviews.
• Proven collaboration with businesses.
• English proficiency at min. B2 level; proficient in Polish.

Skills

Python

SQL

JVM languages

GCP

BigQuery

Spark/Big data

CI/CD

Testing/QA

Business collaboration

Tools

Docker

Kubernetes

Apache Kafka

Apache Airflow

Power BI

Job description

We’re looking for aData Engineerready to push boundaries and grow with us. Datumo specializes in providing Data Engineering and Cloud Computing consulting services to clients from all over the world, primarily in Western Europe, Poland and the USA. Core industries we support includee-commerce,telecommunicationsand life sciences. Our team consists of exceptional people whose commitment allows us to conduct highly demanding projects.

Our team members tend to stick around for more than 3 years, and when a project wraps up, we don't let them go - we embark on a journey to discover exciting new challenges for them. It's not just a workplace; it's a community that grows together!

Must-have:

• at least 3-4 years of commercial experience in programming,
• proven record with a cloud provider - Google Cloud Platform,
• strong knowledge of Python, SQL and JVM languages (Scala or Java or Kotlin),
• experience in BigQuery data warehousing solution,
• in-depth understanding of big data aspects like data storage, modeling, processing, scheduling etc.,
• understanding of Apache Spark (or similar distributed data processing framework),
• ensuring solution quality through automatic tests, CI/CD and code review,
• proven collaboration with businesses,
• English proficiency at min. B2 level, proficient in Polish.

Nice to have:

• knowledge of dbt, Docker and Kubernetes, Apache Kafka,
• familiarity with Apache Airflow or similar pipeline orchestrator,
• another JVM (Java/Scala/Kotlin) programming language,
• experience in Machine Learning projects,
• familiarity with one of BI tools: Power BI/Looker/Tableau,
• willingness to share knowledge (conferences, articles, open-source projects).

What’s on offer:

• 100% remote work, with workation opportunity,
• onboarding with a dedicated mentor,
• project switching possible after a certain period,
• benefits: Medicover Private Medical Care, co-financing of the Medicover Sport card,
• opportunity to learn English with a native speaker,
• regular company trips and informal get-togethers.

Development opportunities in Datumo:

• participation in industry conferences,
• establishing Datumo's online brand presence,
• support in obtaining certifications (e.g. GCP, Azure, Snowflake),
• involvement in internal initiatives, like building technological roadmaps,
• access to internal technological training repositories.

Discover our exemplary project:

IoT data ingestion to cloud

The project integrates data from edge devices into the cloud using Azure services. The platform supports data streaming via either the IoT Edge environment with Java or Python modules, or direct connection using Kafka protocol to Event Hubs. It also facilitates batch data transmission to ADLS. Data transformation from raw telemetry to structured tables is done through Spark jobs in Databricks or data connections and update policies in Azure Data Explorer.

Petabyte-scale data platform migration to Google Cloud

The goal of the project is to improve scalability and performance of the data platform by transitioning over a thousand active pipelines to GCP. The main focus is on rearchitecting existing Spark applications to either Cloud Dataproc or Cloud BigQuery SQL, depending on the Client’s requirements and automate it using Cloud Composer.

Data analytics platform for investing company

The project centers on developing and overseeing a data platform for an asset management company focused on ESG investing. Databricks is the central component. The platform, built on Azure cloud, integrates various Azure services for diverse functionalities. The primary task involves implementing and extending complex ETL processes that enrich investment data, using Spark jobs in Scala. Integrations with external data providers, as well as solutions for improving data quality and optimizing cloud resources, have been implemented.