Senior Data Architect IT
About The Position
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. 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. This is a hybrid position — you will be expected to work from the Warsaw office at least 3 days per week.
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
Nice To Haves
- 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
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
Benefits
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
