Senior Cloud Architect

5 dni temu

Poznań, Greater Poland Datumo Pełny etat
Overview

Datumo is a Big Data and Cloud consulting company that specializes in providing expert services to clients worldwide. With a strong presence in Western Europe, Poland, and the USA, we cater to various industries, including e-commerce, telecommunications, and life sciences.

We take pride in our exceptional team members who are committed to delivering high-quality projects. Our unique approach ensures that our professionals grow together as a community.

Job Description

We are seeking an experienced Senior Cloud Architect/Big Data Engineer Lead to join our team. As a key member of our cloud engineering team, you will design and implement scalable big data systems, leveraging your expertise in cloud providers like GCP, Azure, or AWS.

Your primary focus will be on ensuring solution quality through automated tests, CI/CD pipelines, and code reviews. You will also collaborate with businesses to deliver innovative solutions.

Required Skills and Qualifications
  • A minimum of 3 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) and Python
  • Familiarity with SQL and distributed data processing frameworks like Apache Spark
  • Experience with BigQuery, Snowflake, Hive, or similar distributed datastores
  • Designing and implementing big data systems following best practices
  • Ensuring solution quality through automated testing, CI/CD, and code review
  • Collaboration with businesses
  • English proficiency at B2 level, communicative in Polish
Benefits
  • 100% remote work with workation opportunities
  • 20 free days
  • Dedicated mentor-led onboarding
  • Project switching 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
Exemplary Projects

Our team has worked on exciting projects, including:

IoT Data Ingestion to Cloud

This project integrated data from edge devices into the cloud using Azure services. We designed a platform for data streaming via IoT Edge environments or direct connections using Kafka protocol to Event Hubs. Batch data transmission was facilitated to ADLS, and data transformation from raw telemetry to structured tables was achieved 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 was to improve scalability and performance by transitioning over a thousand active pipelines to GCP. We focused on rearchitecting existing Spark applications to either Cloud Dataproc or Cloud BigQuery SQL, depending on client requirements, and automating it using Cloud Composer.

Data Analytics Platform for Investing Company

This project centered on developing and overseeing a data platform for an asset management company focused on ESG investing. Databricks was the central component, integrating various Azure services for diverse functionalities. We implemented and extended complex ETL processes that enriched investment data using Spark jobs in Scala. Integrations with external data providers and solutions for improving data quality and optimizing cloud resources were also implemented.

Realtime Consumer Data Platform

This initiative involved constructing a consumer data platform (CDP) for a major Polish retail company. We actively participated from the start, contributing to planning the platform's architecture. The CDP was 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, were used to meet specific requirements.

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