Lead Data Engineer (Platform)

TL;DR

Lead Data Engineer (Platform): Design, build, and maintain scalable data engineering frameworks and platform utilities used across engineering teams with an accent on automation, standardization, and reusable patterns. Focus on defining platform architecture, implementing CI/CD pipelines, integrating AI-assisted tools, and leading core data transformation frameworks like dbt Core at enterprise scale.

Location: Sofia (hybrid work options)

Company

Experience innovation company blending data, AI, creativity, and technology to drive transformation for leading brands like L’Oréal, Mars, Audi, P&G, and Volkswagen.

What you will do

• Design, build, and maintain scalable data engineering frameworks, platform utilities, reusable patterns, templates, and abstractions.
• Define and evolve platform architecture, CI/CD pipelines, and automation frameworks to accelerate delivery and improve velocity.
• Lead development and support of core data transformation frameworks like dbt Core, investigate issues, and ensure scalability and consistency.
• Integrate AI-assisted development tools, develop AI engineering assets, and eliminate manual processes through automation.
• Partner with teams to identify pain points, support onboarding, conduct code reviews, and monitor platform health based on metrics.
• Ensure security, compliance, and contribute to documentation and enablement materials.

Requirements

• Strong proficiency in Python for frameworks, automation, and reusable components.
• Hands-on experience with Databricks (notebooks, workflows, jobs, Unity Catalog).
• Strong SQL and distributed processing like Apache Spark; deep dbt Core experience at scale.
• Proven CI/CD pipelines (GitHub Actions, Azure DevOps, GitLab CI); data engineering platform design.
• Software engineering principles (DRY, SOLID); version control, Git workflows; cloud platforms (AWS preferred), IaC (Terraform).
• Automated testing, platform monitoring/logging/alerting, technical documentation; experience in complex multi-team environments.

Nice to have

• Databricks Asset Bundles (DAB); AI tool integration (GitHub Copilot); AI coding standards/prompt engineering.
• Delta Lake, Lakehouse architecture; large-scale platform teams; IAM/secrets/security compliance.
• Driving platform adoption; strong communication and technical leadership.

Culture & Benefits

• Hybrid work flexibility with 25 vacation days for work-life balance.
• Co-subsidized transportation, Multisport cards, premium health insurance.
• Training policy for skills, certifications; personal career development roadmap.
• Self-care program with psychological consultations; cozy office and team events.
• Values-driven culture fostering creativity, diversity, autonomy, and global collaboration.

Hiring process

• Application review by Talent Acquisition based on skills, experience, and potential (no age/gender/photo required).
• Interviews with accommodations available if needed.