GCP Data Architect – Freelance

🕒 September 16

🇵🇱 Poland – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 11%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Lingaro

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2008

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Lingaro is an end-to-end data services and analytics partner for global brands and enterprises, delivering data strategy, platform engineering, AI/ML (including generative AI), and data governance to unlock business value. It combines domain-focused analytics (supply chain, commercial/RGM, digital commerce, sustainability) with data platforms, visualization, MLOps, and secure cloud (Google Cloud) integrations, plus a creative arm (ALCHEMY) for data-driven brand and commerce experience design.

📋 Description

• Collaborate with stakeholders to understand business requirements and translate them into data engineering solutions. • Design and oversee data architecture and infrastructure for scalability, performance, security, maintainability, and industry best practices. • Define data models and schemas based on business needs and data characteristics. • Select and integrate databases, data lakes, data warehouses, and big data frameworks. • Align data engineering solutions with the organization’s long-term data strategy and goals. • Evaluate and recommend data governance strategies, including privacy, security, and compliance measures. • Collaborate with data scientists, analysts, and stakeholders to define data requirements and enable analysis and reporting. • Provide technical guidance to data engineering teams and support implementation by resolving questions and issues. • Oversee implementation according to design documents and technical specifications. • Monitor emerging data engineering technologies and recommend or implement innovative solutions. • Analyze and optimize system performance, resolving bottlenecks and inefficiencies. • Ensure data quality and integrity through validation and monitoring mechanisms. • Integrate data engineering solutions with other systems and applications. • Participate in project planning and estimation. • Document data architecture, infrastructure, and design decisions.

🎯 Requirements

• 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 columnar databases, relational databases, NoSQL databases, data lakes, data warehouses, and big data frameworks. • Knowledge of modern data transformation tools such as DBT and Dataform. • Knowledge of at least one orchestration and scheduling tool. • Programming skills in SQL, Python, and other scripting. • Knowledge of Git, Jira, and Confluence. • Experience selecting and integrating technologies to meet business requirements and long-term data strategy. • Ability to work closely with stakeholders and translate business needs into data engineering solutions. • Strong analytical and problem-solving skills. • Knowledge of data governance principles, data privacy, and security regulations. • Excellent communication and collaboration skills. • Experience leading and mentoring data engineering teams. • Familiarity with agile methodologies and agile development environments. • Continuous learning mindset and awareness of data engineering trends. • Strong project management skills, including prioritization, timeline management, and delivery within deadlines. • Strong understanding of distributed computing principles, including parallel processing, data partitioning, and fault tolerance. • Certifications in big data technologies or cloud platforms, experience with BI solutions, Talend or Alteryx, Apache Spark, Databricks, and Azure are listed as qualifications that would set candidates apart rather than core requirements.

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