Kerja Sepenuh Masa, Data Engineering Team Lead di Michael Page Federal Territory - Maukerja

• Opportunity to be part of the transformational journey
• Embark on a groundbreaking startup journey set to transform global supply chain
  
  

Firmenprofil

Our client haven't just been in the business of supply chain; they have been in the business of re-imagining connections between people and the products they love to create a better future

Aufgabengebiet

• Lead and grow the Data Engineering & ML Engineering team (hiring, onboarding, performance management, coaching, career development).
• Act as a hands-on technical lead (player/coach): drive technical direction, review designs and code, unblock complex engineering problems, and set reusable patterns and standards
• Own end-to-end engineering delivery for data pipelines and curated datasets (data products) on Azure Databricks, ensuring quality, reliability, security and operational readiness.
• Lead ML engineering delivery in partnership with Data Science and MLOps (feature engineering pipelines, training/inference integration, model packaging and deployment readiness, monitoring inputs/outputs).
• Enforce engineering standards: CI/CD, automated testing, code reviews, documentation, data contracts, and data quality validation/reconciliation
  
  

Anforderungsprofil

A Successful Data Engineering Team Lead Should Have

• Core tech stack (hands-on): Azure (ADLS, ADF), Azure Databricks (Spark/Delta/Lakehouse patterns), Python, SQL, Git, CI/CD (Azure DevOps or GitHub), orchestration (ADF and/or Databricks Workflows/Jobs), and observability/monitoring for data pipelines. Preferred: dbt and modern data quality tooling (validation, reconciliation, data contracts
• 8+ years in data and/or software engineering roles, including hands-on delivery on Azure Databricks, with 3+ years of people management
• Solid Python, SQL, and Spark engineering skills (performance tuning, partitioning strategies, cost/performance trade-offs in Databricks jobs and clusters).
  
  

Vergütungspaket

• The People! The Work! The Environment
• Competitive Salary: we offer a salary that reflects your experience, and expertise
• Work-Life Balance: Hybrid Working - 3 days in office, 2 days from home
• Professional Growth: access to ongoing training
• Inclusive Environment: we prioritize diversity and inclusion, ensuring everyone feels welcome and valued.
  
  

If you are passionate about data engineering and leadership and are looking for a permanent role, we encourage you to apply now!

Kontakt

Referenznummer: JN-*************