N-iX

Senior/Lead Data Engineer (Databricks)

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SeniorZdalnieFull-time

#475243·Dodano 10 dni temu·2

Źródło: N-iX

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Tech Stack / Keywords

Databricks CI/CDdata pipelinesdata modelingdata contractsschema evolutionobservabilitydata lineageAI

Podsumowanie oferty

Shape the technical direction of a data platform that makes complex industrial data usable, reliable, and scalable. Build reusable frameworks, internal tools, and automation for data pipelines, while improving data quality, platform reliability, and developer experience.

Wymagania

Data Platform Engineering: Extensive experience designing, building, and evolving scalable data platforms and production data pipelines
Technical Leadership: Experience leading technical design, mentoring engineers, and establishing engineering standards across teams
Programming: Strong software engineering skills, with experience developing reusable frameworks, tooling, and automation for data processing
Data Architecture: Strong understanding of data modeling, schema evolution, data contracts, and validation across multiple source systems
Testing and CI/CD: Practical experience implementing automated testing, integration testing, quality gates, and deployment pipelines
Platform Reliability: Experience improving observability, diagnosing operational issues, and building reliable data services
Data Quality and Lineage: Experience implementing approaches that detect data issues early and make data flows easier to understand and troubleshoot
Developer Experience: Ability to simplify engineering workflows and turn repeated manual work into reusable, maintainable tools
AI-Assisted Engineering: Ability to identify practical AI use cases, evaluate their effectiveness, and define safeguards for quality and reliability
Architectural Judgment: Ability to balance technical quality, delivery speed, operational cost, and long-term maintainability
English Proficiency: C1+ with the ability to communicate technical concepts and architectural decisions clearly
Interpersonal Skills: Strong collaboration skills and the ability to build alignment across engineering teams and domain experts

Obowiązki

Shape the technical direction of the data platform, tooling, and engineering standards
Design and improve reusable frameworks, internal tools, and automation for data pipeline development
Define standards for testing, CI/CD, quality gates, and platform reliability
Develop reusable approaches to data modeling, schemas, data contracts, validation, and schema evolution
Improve observability, data quality, lineage, and developer experience across the platform
Turn recurring delivery challenges into scalable platform capabilities that reduce customer onboarding effort
Apply AI to engineering workflows, establishing clear guardrails and measuring its impact on productivity and quality
Lead technical design discussions, mentor engineers, and guide architectural decisions and technical trade-offs
Document best practices and support the adoption of standard platform patterns across teams
Evaluate architectural decisions against time-to-value, cost-to-serve, and delivery predictability

Benefity

Professional development tools, including a mentorship program, tech talks and trainings, and centers of excellence
Education reimbursement
Corporate events and team buildings
Memorable anniversary presents

Szkolenia wewnętrzne

Dofinansowanie szkoleń

Spotkania integracyjne

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