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Job Description

Description :

What you need :

- 15+ years of experience in data engineering with recent leadership in AI-driven environments.

- Proven ability to design and scale enterprise-grade data architectures, models, and governance frameworks.

- Strong hands-on expertise with Databricks, Airflow, Apache Spark, RDBMS, storage, and cloud platforms (Azure/AWS/GCP).

- Experience transforming legacy systems to modern, cloud-native data platforms and setting CI/CD/MLOps standards.

- Knowledge of LLMs, RAG, vectorization, and modern data compliance/security frameworks (HIPAA/SOC2 preferred).

- Background in DevOps environments, including automation and prior coding experience (.NET, SQL Server).

- Strong people leadership hiring, mentoring, managing multi-location teams, and driving delivery under pressure.

What you would do :


- Lead data engineering strategy and execution for internal platforms and workflows.

- Architect and optimize cloud-based data solutions with a focus on cost and performance.

- Drive development of scalable data platforms and self-service capabilities for cross-functional users.

- Partner with product, engineering, and business leaders to ensure seamless system integration.

- Oversee development quality through code reviews, delivery governance, and KPI tracking.

- Mentor engineers, foster a high-performance culture, and manage escalations and delivery risks.

- Align teams to product vision, ensure accountability, and continuously improve engineering processes.

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