Data Architect
GFT Technologies
contract
Posted on:
Location Type: Hybrid
Location: Warszawa • 🇵🇱 Poland
Visit company websiteSalary
💰 PLN 155 - PLN 205 per hour
Job Level
Mid-LevelSenior
Tech Stack
AWSAzureCloudGoogle Cloud Platform
About the role
- Design and evolve the enterprise data landscape, including data platforms, data integration patterns, and analytical data stores
- Act as a trusted advisor and reference point for data architecture within the organization and for clients, working independently with senior stakeholders
- Define data models, data flows, and architectural standards that support BI, analytical, and AI/ML use cases
- Collaborate with analytics, BI, and ML teams to ensure data architecture effectively support reporting, advanced analytics, and machine learning
- Support pre-sales and client engagements by contributing to data architecture concepts, solution designs, and proposals
- Capture and share best practices in data architecture, data modeling, and platform design across teams
- Ensure that data solutions meet non-functional and regulatory requirements, including security, data quality, governance, lineage, and auditability
Requirements
- Proven experience designing data architectures and building enterprise-scale data landscapes, ideally within financial services
- Strong understanding of how data supports business processes, reporting, analytical decision-making, and regulatory requirements in financial institutions
- Experience with modern data platforms and technologies, including Snowflake and/or Databricks
- Practical knowledge of BI and analytics concepts, tools, and data modeling approaches
- Working knowledge of AI/ML concepts and data requirements for machine learning (feature engineering, data pipelines, training vs inference)
- Experience leveraging public cloud platforms such as AWS, Azure, or GCP
- Knowledge of modern data architectures and patterns, including data lakes, lakehouse architectures, streaming, and event-driven data processing
- Understanding of non-functional requirements such as security, performance, scalability, resilience, and data governance
- Familiarity with regulatory and data governance considerations in financial services (e.g. data privacy, lineage, auditability)
- Excellent communication skills, with the ability to explain data architecture concepts to non-technical audiences and engage senior stakeholders
- Ability to translate business and analytical requirements into robust, scalable, and compliant data architectures
Benefits
- Competitive salary and extra benefit package that can be tailored to your personal needs (private medical coverage, sport & recreation package, lunch subsidy, life insurance, etc.)
- On-line training and certifications fit for career path
- Regular social events
- Access to e-learning platform
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data architecturedata modelingdata integration patternsdata flowsdata platformsBI conceptsanalytics conceptsAI/ML conceptsfeature engineeringdata pipelines
Soft skills
communication skillsstakeholder engagementcollaborationtrusted advisorbest practices sharingtranslating requirements