Data Engineering Lead/ Tech Lead

Job Description

We are seeking an accomplished Lead Data Architect with extensive experience in designing and delivering large-scale data solutions on modern cloud platforms. The ideal candidate will have deep expertise in Snowflake, DBT, and Data Vault 2.0 methodologies, combined with strong technical leadership in data engineering, data modelling, and data governance.

This role will play a pivotal part in defining enterprise data architectures, enabling governed and scalable data ecosystems that drive analytics, AI, and business intelligence initiatives across the organisation.

Key Responsibilities Data Architecture & Engineering

• Lead the design and implementation of enterprise-scale data solutions leveraging modern cloud data platforms to enable scalable and governed data products.
• Architect and implement Data Vault 2.0 methodologies on Snowflake to deliver agile, auditable, and business-driven enterprise data warehouses.
• Define and enforce data modelling standards, naming conventions, and security frameworks to ensure consistent, maintainable, and compliant data architectures.
• Optimise Snowflake performance by designing virtual warehouse strategies, leveraging materialised views, and managing compute and cost governance efficiently. Data Transformation & Automation
• Lead the development of transformation pipelines using DBT, ensuring maintainable, version-controlled, and testable data workflows.
• Implement automated testing, data documentation, and deployment pipelines to maintain transparency in data lineage and ensure high-quality, trusted data outputs.
• Drive adoption of DataOps principles, including CI/CD pipelines, data quality validation frameworks, and GitOps practices for automated deployment.

Advanced Data Engineering

• Utilise Python to build custom data processing frameworks, implement complex business logic beyond SQL capabilities, and integrate data from APIs and diverse source systems.
• Ensure robust data ingestion, orchestration, and monitoring practices across the enterprise data platform.

Stakeholder Engagement & Leadership

• Collaborate with key business and technology stakeholders to identify challenges, define requirements, and translate them into technical architectures.
• Act as a trusted advisor and bridge between technical teams and business units to ensure alignment of priorities and successful delivery of outcomes.
• Foster strong relationships with project managers, IT teams, and business partners to ensure consistent progress toward organisational goals.
• Provide technical mentorship and thought leadership to engineering teams, promoting best practices in data architecture and governance.

Required Skills & Qualifications

• Approximately 15 years of professional experience in data architecture, data engineering, or analytics solutions delivery.
• Proven expertise in Snowflake, DBT, and Data Vault 2.0 methodologies.
• Strong proficiency in Python, SQL, and data integration frameworks.
• Solid understanding of DataOps practices, including CI/CD, automated testing, and infrastructure-as-code (IaC) principles.
• Experience with cloud data platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Strong communication skills with the ability to articulate complex data concepts to both technical and non-technical audiences.
• Demonstrated ability to drive meaningful stakeholder engagement, manage relationships, and deliver measurable business outcomes.
• Active learner with a strong desire to stay updated with emerging data, AI, and cloud technologies.
• Relevant cloud certifications such as Snowflake SnowPro Core/Advanced Architect or Microsoft Certified: Azure Data Engineer Associate are highly desirable.

Education

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related discipline.

Work Model

• Hybrid working arrangement – expected to be at the client office two days per week.

Job Type: Contract

Work Location: Hybrid remote in Warszawa, mazowieckie