Backend Engineer
Principal Data Engineer / Data Architect
Remotelead
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Organisation/Department
Our client is a US-headquartered, market-leading enterprise in their sector with a multi-decade history and an agile, global network. We are seeking a highly skilled
Principal Data Engineer
to join their expanding Budapest team as a senior technical individual contributor. In this role, you will define data platform architecture and directly shape future-proof, data-driven, and AI-enabled solutions.
Job description
- Architecture & Implementation:
Architect and implement production-grade data solutions on AWS and Databricks — from lakehouse design through pipeline delivery, ensuring high performance, reliability, and cost efficiency. - Technical Strategy & Standards:
Translate the overall data strategy into concrete technical blueprints, reference architectures, and actionable implementation plans. Establish and enforce architectural standards, data modeling conventions, and engineering best practices. - Data Platform Foundations:
Own the design and buildout of core data platform components — including ingestion frameworks, transformation layers, data quality enforcement, and serving patterns. - ML/AI Enablement:
Design data pipelines and lakehouse structures that directly enable Machine Learning and AI workloads, collaborating closely with Data Science and MLOps teams. - Platform FinOps:
Drive FinOps at the architecture level — right-sizing compute/storage, building cost attribution models, and implementing cost optimization patterns across the platform. - Technical Mentorship:
Mentor data engineers through architectural guidance, pair programming, and code reviews without carrying people-management responsibilities.
Requirements
- Core Experience:
6+ years as a hands-on data engineer or data architect with recent, demonstrated production delivery in modern cloud-native stacks. - Senior / Principal Track:
3+ years operating at a Staff, Principal, or Senior Architect level as an individual contributor driving technical direction. - Databricks & AWS Expertise:
Deep production experience with the
Databricks Lakehouse on AWS
—
Unity Catalog, Delta Live Tables, Databricks SQL, Databricks Workflows, and Structured Streaming
. Strong working knowledge of supporting AWS services (
S3, IAM, Glue, Lambda, Kinesis, Redshift
). - Data Modeling & Observability:
Expert-level data modeling skills (Dimensional, Data Vault, Lakehouse paradigms) and proven experience building data quality frameworks and automated testing into pipeline architectures. - Infrastructure-as-Code:
Proficiency with
Terraform, CloudFormation,
or
Databricks Asset Bundles
. - FinOps Approach:
Hands-on experience designing architectures that control compute spend and optimize resource utilization.
Preferred Qualifications:
- Production experience building data infrastructure that directly enabled ML/AI product features (e.g., feature engineering pipelines, training datasets, model monitoring).
- Experience with real-time or near-real-time data architectures (streaming ingestion, CDC, event-driven patterns).
- Familiarity with Data Mesh principles, domain-oriented platform design, and enterprise data governance (access controls, PII handling, lineage).
Benefits
- High Technical Impact:
A unique professional challenge to shape the core data platform for a stable, market-leading global enterprise. - Competitive Compensation:
Senior/Principal level base salary and annual target bonus. - Benefits Package:
Cafeteria allowance and private health insurance package. - Flexibility:
Hybrid working model requiring 3 days of office presence (Budapest) and offering 2 days of Home Office per week.
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