Type of contract: B2B contract 

Salary range: 200-265 PLN/H

What will you do?

As a Data Architect, you will combine deep data architecture expertise with hands-on experience in modern data platforms, analytics, and cloud technologies. You will advise stakeholders and translate business, data, and analytical requirements into secure, scalable, governed, and high-performing end-to-end data solutions.

You will own the technical design and architectural success of data and analytics initiatives, from data ingestion and integration through storage, transformation, governance, reporting, advanced analytics, and consumption. You will ensure that data is trusted, accessible, well-managed, and capable of supporting operational reporting, self-service analytics, machine learning, and AI use cases.

This role requires understanding how decisions across data sources, integration patterns, data models, platforms, security, governance, and consumption layers affect the overall analytical ecosystem. You will develop deep expertise in enterprise data architecture, cloud data platforms, data management, and analytics delivery.

Your tasks

• Act as a trusted advisor and reference point for enterprise data, analytics, and data governance solutions within the organization and for clients. Work independently with senior business and technology stakeholders.
• Lead and support the end-to-end design and delivery of analytical solutions, including data ingestion, data lakes/lakehouses, data warehouses, semantic layers, BI, and advanced analytics platforms.
• Translate business requirements into scalable data architectures, logical and physical data models, data integration designs, and analytical solution blueprints.
• Define and promote data architecture standards, principles, reference architectures, reusable patterns, and best practices across teams.
• Design data platforms that enable reliable, timely, secure, and high-quality access to data for reporting, dashboards, self-service analytics, machine learning, and AI workloads.
• Establish approaches for data governance, data quality, metadata management, master data management, lineage, data ownership, and data lifecycle management.
• Collaborate with data engineers, analytics engineers, data scientists, BI developers, platform teams, security teams, and business stakeholders to ensure successful solution delivery.
• Support pre-sales and client engagements by shaping data and analytics offerings, developing proposals, estimating solutions, and presenting architectures to senior stakeholders.
• Capture and share best practices in data architecture and analytical solution design, contributing to the continuous evolution of the organization’s data and analytics portfolio.

Your skills

• Strong experience in designing and building modern enterprise data and analytics solutions, including data warehouses, data lakes, lakehouses, data marts, and self-service analytics platforms.
• Proven background in data architecture, with the ability to design end-to-end data ecosystems integrating multiple source systems, cloud platforms, analytical tools, and consumption channels.
• Experience with data modeling techniques, including conceptual, logical, and physical data models, dimensional modeling, data vault, normalization, and semantic-layer design.
• Practical experience with data integration and transformation technologies, including ETL/ELT, batch and real-time processing, data pipelines, APIs, event streaming, and change data capture.
• Strong knowledge of cloud data and analytics services on at least one leading public cloud provider: AWS, Microsoft Azure, or Google Cloud Platform.
• Experience with modern data platforms and technologies such as Databricks, Snowflake, Microsoft Fabric, Azure Synapse, BigQuery, Redshift, or equivalent tools.
• Knowledge of data engineering and orchestration tools, such as Apache Spark, dbt, Airflow, Azure Data Factory, AWS Glue, Informatica, Talend, or similar technologies.
• Experience with streaming and event-driven data architectures, including technologies such as Kafka, Event Hubs, Kinesis, or Pub/Sub.
• Strong understanding of data governance, data quality, metadata, lineage, cataloguing, privacy, retention, and regulatory compliance requirements.
• Ability to design secure data solutions, including identity and access management, role-based access control, encryption, data masking, row- and column-level security, and sensitive-data protection.
• Understanding of non-functional requirements, including performance, scalability, availability, resilience, observability, cost optimization, recoverability, and operational supportability.
• Familiarity with BI and analytics tools, such as Power BI, Tableau, Qlik, Looker, or equivalent platforms, including semantic models and governed self-service reporting.
• Understanding of how data platforms support machine learning, AI, and advanced analytics use cases, including feature engineering, MLOps, model data pipelines, and access to governed analytical datasets.
• Familiarity with Agile delivery methods, DevOps and DataOps practices, CI/CD pipelines, infrastructure as code, automated testing, and version control.
• Excellent communication and stakeholder-management skills, with the ability to explain complex data concepts to technical and non-technical audiences.
• Ability to support sales, offering development, and client engagements by creating proposals, architecture diagrams, roadmaps, and solution blueprints.
• Advanced knowledge across relevant IT domains, including cloud infrastructure, networking, security, identity, integration, application architecture, business continuity, disaster recovery, data management, budgeting, and governance.
• Previous experience in banking, financial services, insurance, fintech, or other highly regulated industries is highly desirable.