Big Data Engineer with Cloud Expertise
3 dni temu
About Datumo
Datumo is a leading Big Data and Cloud consulting services provider, serving clients globally, particularly in Western Europe, Poland, and the USA. Our core industries include e-commerce, telecommunications, and life science.
Our team boasts exceptional individuals committed to delivering high-demanding projects. Team members tend to stay for more than three years, and when projects wrap up, we embark on new challenges together, fostering a sense of community.
Job Overview
We are seeking a skilled Data Engineer with Cloud Expertise to join our team. The successful candidate will have extensive experience in Big Data and cloud platforms, including GCP, Azure, or AWS.
Salary Estimate
We offer an estimated annual salary range of $120,000 - $180,000, depending on location and experience.
Required Skills and Qualifications
- A minimum of three years of commercial experience in Big Data
- Proven record with a selected cloud provider (GCP preferred, Azure, or AWS)
- Strong knowledge of JVM languages (Scala, Java, or Kotlin)
- Good understanding of Python
- Familiarity with SQL
- Understanding of Apache Spark or similar distributed data processing frameworks
- Experience with BigQuery, Snowflake, Hive, or similar distributed datastores
- Ability to design and implement Big Data systems following best practices
- Ensuring solution quality through automatic tests, CI/CD, and code review
- Proven collaboration with businesses
- English proficiency at B2 level, communicative in Polish
Benefits
- 100% remote work with workation opportunities
- 20 free days off
- Onboarding with a dedicated mentor
- Project switching possible after a certain period
- Individual budget for training and conferences
- 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 gatherings
Development Opportunities
- Participation in industry conferences
- Establishing Datumo's online brand presence
- Support in obtaining certifications (e.g., GCP, Azure, Snowflake)
- Involvement in internal initiatives, such as building technological roadmaps
- Training budget
- Access to internal technological training repositories
Notable Projects
Datumo has worked on various notable projects, including:
IOT data ingestion to cloud
The project integrates data from edge devices into the cloud using Azure services. It supports data streaming via IoT Edge environments or direct connection using Kafka protocol to Event Hubs. Batch data transmission to ADLS is also facilitated. 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 this project is to improve scalability and performance of the data platform by transitioning over a thousand active pipelines to GCP. Re-architecting existing Spark applications to Cloud Dataproc or Cloud BigQuery SQL, depending on client requirements, and automating it using Cloud Composer is the main focus.
Data analytics platform for investing company
This 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. Implementing and extending complex ETL processes that enrich investment data using Spark jobs in Scala is the primary task. Integrations with external data providers and solutions for improving data quality and optimizing cloud resources have been implemented.
Realtime Consumer Data Platform
This initiative involves constructing a consumer data platform (CDP) for a major Polish retail company. Datumo actively participates from the start, contributing to planning the platform's architecture. The CDP is built on Google Cloud Platform (GCP), utilizing services like Pub/Sub, Dataflow, and BigQuery. Open-source tools, including a Kubernetes cluster with Apache Kafka, Apache Airflow, and Apache Flink, are used to meet specific requirements.
Recruitment Process
- Quiz - 15 minutes
- Soft skills interview - 30 minutes
- Technical interview - 60 minutes
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