Senior Data Engineer (Databricks)
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Summary
Builds and maintains scalable data pipelines on Databricks and Apache Spark, integrating diverse data sources and optimizing for performance and cost.
- Design, develop, and maintain scalable data pipelines using Databricks and Apache Spark.
- Define data architectures that support batch and streaming processing.
- Integrate data from multiple sources, including databases, APIs, and cloud storage.
- Optimize data solutions for performance, reliability, and cost efficiency.
- Collaborate closely with data science, analytics, and business teams.
- Provide technical leadership and guidance on data engineering best practices.
- Translate complex Databricks architectures and data solutions into clear, business-friendly explanations for technical and non-technical audiences.
- Document data architectures, pipelines, and technical decisions.
- Support production systems and troubleshoot data-related issues as needed.
- Minimum of 5 years of experience as a Data Engineer or in a similar role.
- Strong hands-on experience with Databricks and Apache Spark.
- Advanced SQL and Python skills.
- Experience working in cloud environments (Azure preferred).
- Solid understanding of data modeling, ETL/ELT processes, and data architecture concepts.
- Ability to work independently while collaborating with distributed teams.
• Competitive salary
• Flexible work environment
• Opportunities for growth and certifications
• Inclusive and collaborative team culture
• Access to cutting-edge tools and technologies