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Salary
$76k – $92k per year
Location
Remote (Poland)
Seniority
Senior · 5+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Spyrosoft is a global technology group founded in 2016 that specializes in digital transformation and custom software engineering for clients worldwide. The company provides a comprehensive suite of services, including product design, AI/ML, cloud solutions, and embedded systems, across diverse industries such as automotive, finance, healthcare, and robotics. Listed on the Warsaw Stock Exchange, the group operates as a network of specialized companies that empower businesses to scale and thrive through innovative technology.

Tech stack:

  • Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, etc.)

  • BI/ETL Tools & Big Data Technologies

  • Relational Databases (SQL) & NoSQL/Big Data storage

  • Data Vault 2.0, Data Mesh, Data Fabric

Requirements:

  • 5+ years of hands-on experience building complex, production-grade data solutions.

  • 3+ years of dedicated experience within the Google Cloud Platform ecosystem.

  • Proven track record with BI/ETL and Big Data technologies.

  • Strong understanding of relational database design and big data architectural patterns.

  • Experience with real-time data processing and sophisticated data warehousing aggregation.

  • Deep understanding of Data Fabric, Data Mesh, and Data Vault methodologies.

  • Ability to lead technical discussions and explain complex architectural choices to stakeholders.

Project description:

We are looking for a Senior Data Engineer to join our team and lead the design and implementation of high-performance, scalable data architectures. You will be a key player in shaping our data ecosystem, leveraging the full power of Google Cloud Platform (GCP) to solve complex business challenges.

Main responsibilities:

  • Design and develop end-to-end, complex data solutions and ETL/ELT pipelines.

  • Utilize GCP services to manage big data workloads and real-time processing.

  • Implement data warehousing aggregations and real-time streaming solutions.

  • Facilitate design discussions, document architectural decisions, and ensure best practices across the data lifecycle.

  • Apply Data Vault, Data Mesh, and Data Fabric principles to create a future-proof data environment.

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