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PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

Google Cloud Data Architect

Data EngineeringConfirmed live in the last 24 hours
Full-timeWarsaw, PolandNo salary listed

About the Job

Requirements

  • At least 3 years of experience designing and implementing data-based solutions, including at least 2 years of experience with Google Cloud Platform.
  • In-depth knowledge of Google Cloud Platform services, particularly BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Composer/Airflow, and Cloud Functions.
  • Proficiency in SQL and at least one of Python, Java, or Scala.
  • Experience designing and building data warehouses, data lakes, and Data Mesh or Data Lakehouse architectures.
  • Understanding of cloud data security and data governance, with the ability to apply them in practice.
  • Experience with Infrastructure as Code technologies such as Terraform and CI/CD tools such as Jenkins, GitLab CI, Cloud Build, or GitHub Actions.
  • Active use of artificial intelligence tools to improve work quality and pace.
  • Ability to conduct technical and business-level client conversations, present solutions, recommend approaches, and build trust as an architect-advisor.
  • Ability to communicate fluently in Polish and English at a minimum B2 level.

Responsibilities

  • Create comprehensive data architecture designs in Google Cloud Platform, accounting for business requirements, scalability, performance, security, and cost optimization.
  • Implement solutions using Google Cloud Platform services, including BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Composer/Airflow, and Cloud Functions.
  • Design and implement reliable, high-performance data pipelines for processing, transforming, and loading data (ETL/ELT), from batch processing through real-time streaming.
  • Design data warehouses, data lakes, and data lakehouses using data-modeling best practices.
  • Monitor, analyze, and optimize the performance of existing data solutions in Google Cloud Platform by identifying bottlenecks and implementing improvements.
  • Plan and execute data migrations to Google Cloud Platform and between cloud platforms.
  • Create multi-cloud and platform-agnostic solutions using Azure, AWS, Databricks, dbt, and Apache Spark.
  • Implement Infrastructure as Code solutions using DevOps and CI/CD practices.
  • Actively use artificial intelligence tools such as Gemini, Claude, and Copilot to improve daily engineering efficiency.
  • Lead client discussions, present architectural solutions, explain technical decisions in terms of business benefits, and build relationships as a trusted technology advisor.

Desired Qualifications

  • Knowledge of data solutions in other public clouds, such as Microsoft Azure (including Azure Synapse Analytics, Azure Data Factory, or Azure Databricks) or Amazon Web Services (including Amazon Redshift, AWS Glue, or Amazon EMR).
  • Experience with Teradata, Databricks, dbt, Apache Kafka, or Apache Spark in on-premises and multi-cloud environments.
  • Google Cloud Professional Data Engineer or Professional Cloud Architect certification, or equivalent.
  • Experience in consulting or project work involving direct client contact.
  • Knowledge of AI/ML and generative AI solutions, including Vertex AI and BigQuery ML, to support AI implementations in data platforms.

About the Company

PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

PwC provides assurance (audit), tax, legal services, consulting and deals advisory to organisations worldwide. It uses multidisciplinary teams across accounting, advisory, technology and industry, delivered through a global network of locally established firms that collaborate with technology partners to offer AI, cloud, managed services and digital trust. PwC differentiates itself with an integrated, global-local service model and technology-enabled offerings that address complex client needs across risk, transformation, reporting and sustainability. Its goal is to help clients improve governance, efficiency and value by supporting reporting accuracy, business transformation, risk management and sustainable practices.

Company size
10,001+
Company stage
Early VC
Total funding
$3.3M
Headquarters
London, United Kingdom
Founded
1989

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