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-052026-7017012