GCP Data Architect

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Tasks

• • Collaborate with stakeholders to understand business requirements and translate them into data engineering solutions.
  • Design and oversee the overall data architecture and infrastructure, ensuring scalability, performance, security, maintainability, and adherence to industry best practices.
  • Define data models and data schemas to meet business needs, considering factors such as data volume, velocity, variety, and veracity.
  • Select and integrate appropriate data technologies and tools, such as databases, data lakes, data warehouses, and big data frameworks, to support data processing and analysis.
  • Ensure that data engineering solutions align with the organization's long-term data strategy and goals.
  • Evaluate and recommend data governance strategies and practices, including data privacy, security, and compliance measures.
  • Collaborate with data scientists, analysts, and other stakeholders to define data requirements and enable effective data analysis and reporting.
  • Provide technical guidance and expertise to data engineering teams, promoting best practices, and ensuring high-quality deliverables. Support to team throughout the implementation process, answering questions and addressing issues as they arise.
  • Oversee the implementation of the solution, ensuring that it is implemented according to the design documents and technical specifications.
  • Stay updated with emerging trends and technologies in data engineering, recommending, and implementing innovative solutions as appropriate.
  • Conduct performance analysis and optimization of data engineering systems, identifying and resolving bottlenecks and inefficiencies.
  • Ensure data quality and integrity throughout the data engineering processes, implementing appropriate validation and monitoring mechanisms.
  • Collaborate with cross-functional teams to integrate data engineering solutions with other systems and applications.
  • Participate in project planning and estimation, providing technical insights and recommendations.
  • Document data architecture, infrastructure, and design decisions, ensuring clear and up-to-date documentation for implementation, reference, and knowledge sharing.

Requirements

• What We're looking for:

  • At least 6 years of experience as Data Architect, including min. 4 years of experience working with GCP cloud-based infrastructure & systems.
  • Deep knowledge of Google Cloud Platform and cloud computing services.
  • Strong experience in the Data & Analytics area.
  • Strong understanding of data engineering concepts, including data modeling, ETL processes, data pipelines, and data governance.
  • Expertise in designing and implementing scalable and efficient data processing frameworks.
  • In-depth knowledge of various data technologies and tools, such as columnar databases, relational databases, NoSQL databases, data lakes, data warehouses, and big data frameworks.
  • Knowledge of modern data transformation tools (such as DBT, Dataform).
  • Knowledge of at least one orchestration and scheduling tool.
  • Programming skills (SQL, Python, other scripting).
  • Tools knowledge: Git, Jira, Confluence, etc.
  • Experience in selecting and integrating appropriate technologies to meet business requirements and long-term data strategy.
  • Ability to work closely with stakeholders to understand business needs and translate them into data engineering solutions.
  • Strong analytical and problem-solving skills, with the ability to identify and address complex data engineering challenges.
  • Knowledge of data governance principles and best practices, including data privacy and security regulations.
  • Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.
  • Experience in leading and mentoring data engineering teams, providing guidance and technical expertise.
  • Familiarity with agile methodologies and experience in working in agile development environments.
  • Continuous learning mindset, staying updated with the latest advancements and trends in data engineering and related technologies.
  • Strong project management skills, with the ability to prioritize tasks, manage timelines, and deliver high-quality results within designated deadlines.
  • Strong understanding of distributed computing principles, including parallel processing, data partitioning, and fault-tolerance.

  What Will Set You Apart:

  • Certifications in big data technologies or/and cloud platforms.
  • Experience with BI solutions (e.g. Looker, Power BI, Tableau).
  • Experience with ETL tools: e.g. Talend, Alteryx
  • Experience with Apache Spark, especially in GCP environment.
  • Experience with Databricks.
  • Experience with Azure cloud-based infrastructure & systems.

  Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow.