About the Role
<h4><strong>Senior Data Architect – </strong> <strong>Cloud Data Architecture & Governance</strong></h4><p>📍 Hybrid in Warsaw (3 days/week onsite required) | 💼 Full-time | B2B contract up to $8,000/month</p><h5><strong>About the Role</strong></h5><p>Our client is a US-based leader in AI-powered enterprise operations, delivering digital solutions and consulting services that transform high-growth businesses and private equity-backed platforms. With over a decade of deep domain expertise in private capital markets, the company operates an integrated ecosystem spanning PaaS, SaaS, and a Solutions & Consulting Suite.</p><p>We are seeking a Senior Data Architect to join the company's growing Warsaw engineering centre. In this role you will own enterprise data architecture from strategy through execution — designing cloud-native data platforms, establishing governance standards, and enabling AI/ML-ready data infrastructure that powers business intelligence across the portfolio.</p><p><em>This is a hybrid position — you will be expected to work from the Warsaw office at least 3 days per week.</em></p><h5><strong>Key Responsibilities</strong></h5><ul><li><p>Design, develop, and maintain enterprise data architecture strategies, standards, and blueprints supporting operational, analytical, and AI/ML workloads</p></li><li><p>Architect cloud-native data solutions on AWS (Redshift, RDS, Glue, Lake Formation) or equivalent platforms, ensuring scalability, security, and cost efficiency</p></li><li><p>Define and enforce data modeling standards: dimensional modeling, denormalized schemas, OLTP/OLAP design patterns, and AI-friendly ontologies</p></li><li><p>Architect and oversee data transformation layers using DBT, delivering modular, tested, and well-documented models across the analytics stack</p></li><li><p>Lead design of data integration and orchestration patterns with Prefect and Airflow — batch ETL, real-time streaming, event-driven, and API-based data exchange</p></li><li><p>Define and implement data validation, quality control, and automated testing frameworks across pipelines and warehouses</p></li><li><p>Establish data quality SLAs, monitoring, and alerting standards; design automated reconciliation processes to catch issues before downstream impact</p></li><li><p>Build and maintain data governance frameworks: data quality, lineage, cataloging, classification, and access control</p></li><li><p>Collaborate with Data Engineers, Software Engineers, Product, and Analytics teams to translate business requirements into scalable designs</p></li><li><p>Evaluate and recommend data technologies and tools; own technical decision-making for data infrastructure within assigned domains</p></li><li><p>Design data partitioning, indexing, and optimization strategies for high-performance queries and big data workloads</p></li><li><p>Ensure architectures support AI/ML consumption — feature stores, embedding pipelines, and model training datasets</p></li><li><p>Perform architecture and code reviews to uphold data standards, optimal execution patterns, and long-term maintainability</p></li><li><p>Mentor data engineers on best practices in modeling, architecture patterns, and cloud data design</p></li><li><p>Assist with CI/CD processes and automated release management for data infrastructure deployments</p></li></ul><h5><strong>Key Requirements</strong></h5><ul><li><p>7+ years of experience in data architecture, data engineering, or related technical roles</p></li><li><p>5+ years designing and implementing cloud-based data architectures (AWS, GCP, or Azure)</p></li><li><p>5+ years writing complex SQL queries across RDBMSes</p></li><li><p>5+ years developing and deploying ETL/ELT pipelines using Airflow, Prefect, or similar tools</p></li><li><p>Strong experience with DBT for data transformation, testing, and documentation</p></li><li><p>Experience with data warehouse design: OLTP, OLAP, star schemas, snowflake schemas, dimensions, and facts</p></li><li><p>Experience with data modeling tools and methodologies (conceptual, logical, physical models)</p></li><li><p>Hands-on experience with cloud-based data warehouses such as Redshift, Snowflake, or BigQuery</p></li><li><p>Experience implementing data validation frameworks, quality control processes, and automated testing for data pipelines</p></li><li><p>Familiarity with how data architectures serve AI/ML workloads, including feature stores and vector-based retrieval patterns</p></li><li><p>Strong understanding of data governance, data quality frameworks, and metadata management</p></li><li><p>Bachelor's degree in Computer Science or equivalent — preferred<br></p></li></ul><h5><strong>Nice to Have</strong></h5><p>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</p><h5><strong>What's Offered</strong></h5><ul><li><p>B2B contract with monthly compensation up to $8,000</p></li><li><p>Strategic, high-ownership role in a fast-growing global fintech</p></li><li><p>Direct influence over data infrastructure decisions and team direction</p></li><li><p>Mentorship opportunities and clear career progression</p></li><li><p>Collaborative, open, and ambitious team culture</p></li><li><p>Hybrid model — minimum 3 days/week in the Warsaw office</p></li></ul>