Data Engineer
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Job description
We are seeking a highly skilled Data Engineer to design, build, and optimize enterprise-grade data solutions leveraging Databricks and modern cloud technologies. This role will lead data solutions, data engineers, ensuring scalable, secure, and efficient data pipelines that power analytics and business intelligence across the division, * Design and develop data pipelines using Databricks Lakehouse architecture, including ingestion, transformation, and orchestration layers.
- Implement Medallion architecture (Bronze, Silver, Gold layers) and manage data lineage, quality, and governance using Unity Catalog.
- Drive adoption of best practices for data governance, metadata management, and cost optimization.
- Mentor and guide junior engineers, ensuring adherence to coding standards and architectural principles.
- Collaborate with cross-functional teams (data scientists, analysts, business stakeholders) to translate requirements into technical solutions.
- Automate workflows for data ingestion and transformation using Databricks Jobs and orchestration tools.
- Monitor and troubleshoot performance issues across pipelines and clusters.
- Implement robust data security measures, including encryption, access controls, and auditing.
- Stay current with emerging technologies and recommend improvements to enhance scalability and efficiency.
Requirements
Experienced Senior Data Engineer with over 3 years of Databricks expertise.
- Strong hands-on expertise with Databricks, including:
- Spark (PySpark or Spark SQL)
- Delta Lake
- Data Lakehouse architecture
- Unity Catalog
- Proficiency in Python and SQL for data engineering workflows.
- Databricks Certified Data Engineer Professional (or equivalent) is mandatory.
- Familiarity with CI/CD practices and infrastructure-as-code.
Preferred Qualifications
- Experience with DBT for transformation and dependency management.
- Azure Data Engineer Associate or AWS certifications are often preferred.
- Knowledge of data governance frameworks and observability tools.
- Exposure to machine learning pipelines and MLflow is a plus.
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