Datatonic

Principal Data Engineer

Datatonic

full-time

Posted on:

Location Type: Hybrid

Location: Zagreb • 🇭🇷 Croatia

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Job Level

Lead

Tech Stack

BigQueryCloudDockerKubernetes

About the role

  • Leadership and accountability for the technical roadmap of services
  • Implement and execute on the tooling strategy required to delivery a highly automated and scalable data managed service
  • Support the sales team with technical pre-sales enablement including build out pitch decks, architecture documents and sales collateral
  • Advise consulting teams on best practices for build of data platforms that are considerate of managed services
  • Working closely with OCTO (Office of the CTO) to ensure close alignment on existing and new standards
  • Being an advocate for and keeping up to date with new technologies, Google services, and the evolution of GenAI
  • Senior escalation point for intractable issues with customer platforms
  • Work with the Head of Managed Services on the strategic objectives of the Data Operations team
  • Contributing to development and evolution of the services portfolio
  • Coaching and mentoring junior technical staff, including responsibility for defining learning paths for engineering teams
  • Promote growth and continuous development of engineering teams

Requirements

  • Strong commercial awareness of Data Managed Services solutions, particularly with scoping and pitching to large enterprise customers including pricing, contracts and proposals
  • Strong interpersonal skills with the ability to work with clients to establish requirements in non-technical language
  • Ability to translate business requirements into plausible technical solutions for articulation to engineering teams
  • Ability to understand existing target architecture and adjust accordingly to accommodate new business requirements
  • Strong experience in monitoring and measuring platform performance and availability e.g SLO and SLI
  • Experience managing across relationships across internal and external customers, stakeholders and executives
  • Experience with Google Data Products tools (e.g., BigQuery, Dataflow, DataProc, Dataplex, Composer, Vertex, Looker, etc.)
  • Experience building and deploying solutions to Cloud (Google Cloud) including Cloud provisioning tools and management of releases through various environments into production
  • Experience and knowledge of application containerisation e.g. Docker, Kubernetes, Cloud Run, etc
  • Deep expertise with data warehousing (Kimball, Lakehouse, Data Mesh), particularly Big Query built using dbt/Dataform
  • Ability to work on resolving and anticipating complex issues that might impact multiple stakeholders
  • Experience of working CI/CD technologies, Git, Github Actions, Cloud Build, etc
  • Google cloud certifications: Cloud Architect Professional or Data Engineer Professional or Machine Learning Professional
Benefits
  • Health insurance
  • Flexible working arrangements
  • Professional development opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
data managed servicesplatform performance monitoringapplication containerizationdata warehousingCI/CD technologiesGoogle Cloud provisioningtechnical pre-sales enablementarchitecture documentationdata platform best practicesbusiness requirements translation
Soft skills
leadershipaccountabilityinterpersonal skillscoachingmentoringcommunicationproblem-solvingcollaborationstrategic thinkingclient relationship management
Certifications
Cloud Architect ProfessionalData Engineer ProfessionalMachine Learning Professional