Job Description

Job Title: Senior Databricks Engineer

Location: Remote

Duration/Term: Long Term Contract



Job Summary:

We are seeking an experienced Databricks Engineer with a strong background in Databricks, Apache Spark, and big data ecosystem tools . You will lead the design and development of scalable data pipelines, architect efficient data models, and mentor junior engineers-ensuring performance, reliability, and governance across cloud-native infrastructure.

Key Responsibilities:

• Design and develop data processing pipelines and analytics solutions using Databricks.
• Architect scalable, efficient, and secure data models and storage frameworks on the Databricks platform.
• Collaborate with architecture and engineering teams to migrate legacy solutions to Databricks.
• Optimize Databricks clusters and job performance to meet SLAs and business needs.
• Enforce best practices for data governance, privacy, security, and compliance .
• Mentor junior engineers and offer technical guidance and code reviews .
• Stay current with data engineering trends, tools, and emerging technologies to drive innovation and excellence.

Required Qualifications:

• 9+ years of overall experience in data engineering or software development.
• 4+ years hands-on experience with Databricks and Apache Spark platforms.
• Proficiency in Python , Scala , or SQL for building data pipelines.
• Solid understanding of distributed computing concepts and big data architecture .
• Experience with at least one major cloud platform ( AWS, Azure, or GCP ) and relevant data services.
• Proven track record of delivering scalable and reliable data solutions .
• Strong analytical mindset, attention to detail, and problem-solving skills.
• Excellent communication skills and ability to work across cross-functional teams.

Preferred Qualifications:

• Experience with Docker, Kubernetes , or similar containerization/orchestration tools.
• Familiarity with DevOps practices for automated deployment, monitoring, and CI/CD workflows.

Key Skills:

Databricks, Apache Spark, Python, Scala, SQL, Cloud Platforms (AWS, Azure, GCP), Data Pipeline Architecture, Big Data Engineering, Data Governance, Distributed Systems, Containerization (Docker/Kubernetes), CI/CD, DevOps Practices.

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