Senior Data Architect IT

Technologies we use

About the project

Your responsibilities

• Design, develop, and maintain enterprise data architecture strategies, standards, and blueprints supporting operational, analytical, and AI/ML workloads
• Architect cloud-native data solutions on AWS (Redshift, RDS, Glue, Lake Formation) or equivalent platforms, ensuring scalability, security, and cost efficiency
• Define and enforce data modeling standards: dimensional modeling, denormalized schemas, OLTP/OLAP design patterns, and AI-friendly ontologies
• Architect and oversee data transformation layers using DBT, delivering modular, tested, and well-documented models across the analytics stack
• Lead design of data integration and orchestration patterns with Prefect and Airflow — batch ETL, real-time streaming, event-driven, and API-based data exchange
• Define and implement data validation, quality control, and automated testing frameworks across pipelines and warehouses
• Establish data quality SLAs, monitoring, and alerting standards; design automated reconciliation processes to catch issues before downstream impact
• Build and maintain data governance frameworks: data quality, lineage, cataloging, classification, and access control
• Collaborate with Data Engineers, Software Engineers, Product, and Analytics teams to translate business requirements into scalable designs
• Evaluate and recommend data technologies and tools; own technical decision-making for data infrastructure within assigned domains
• Design data partitioning, indexing, and optimization strategies for high-performance queries and big data workloads
• Ensure architectures support AI/ML consumption — feature stores, embedding pipelines, and model training datasets
• Perform architecture and code reviews to uphold data standards, optimal execution patterns, and long-term maintainability
• Mentor data engineers on best practices in modeling, architecture patterns, and cloud data design
• Assist with CI/CD processes and automated release management for data infrastructure deployments

Our requirements

• 7+ years of experience in data architecture, data engineering, or related technical roles
• 5+ years designing and implementing cloud-based data architectures (AWS, GCP, or Azure)
• 5+ years writing complex SQL queries across RDBMSes
• 5+ years developing and deploying ETL/ELT pipelines using Airflow, Prefect, or similar tools
• Strong experience with DBT for data transformation, testing, and documentation
• Experience with data warehouse design: OLTP, OLAP, star schemas, snowflake schemas, dimensions, and facts
• Experience with data modeling tools and methodologies (conceptual, logical, physical models)
• Hands-on experience with cloud-based data warehouses such as Redshift, Snowflake, or BigQuery
• Experience implementing data validation frameworks, quality control processes, and automated testing for data pipelines
• Familiarity with how data architectures serve AI/ML workloads, including feature stores and vector-based retrieval patterns
• Strong understanding of data governance, data quality frameworks, and metadata management
• Bachelor's degree in Computer Science or equivalent — preferred

Optional

• Python / Pandas / PySpark · Docker · Kubernetes · CI/CD Automation · AWS Lambdas / Step Functions · Data Partitioning · Databricks · Vector Databases (Pinecone, Weaviate, pgvector) · Data Mesh / Data Fabric · Graph Databases / Knowledge Graph Design · Cloud Certifications

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What we offer

• B2B contract with monthly compensation up to $8,000
• Strategic, high-ownership role in a fast-growing global fintech
• Direct influence over data infrastructure decisions and team direction
• Mentorship opportunities and clear career progression
• Collaborative, open, and ambitious team culture
• Hybrid model — minimum 3 days/week in the Warsaw office

Benefits