Data Engineer

What is expected of you at this level:

What you must have :

• 4+ years of data engineering experience, building and managing large-scale data pipelines
• Strong proficiency in Python, PySpark, Spark, Databricks, Delta Lake, and SQL, with hands-on experience using Azure Data
• Factory, Azure Pipelines, Azure DevOps, and Git for version control.
• Proven experience working with Azure Databricks and PySpark/Spark for data engineering tasks
• In-depth knowledge of performance optimization techniques for large-scale data processing, including code tuning and resource management
• Solid understanding of data modeling and working with complex data types (arrays, structs, maps)
• Hands-on experience implementing CI/CD pipelines with Azure DevOps, GitHub Actions, or similar tools
• Excellent problem-solving, debugging, and troubleshooting skills
• Collaborate with data engineers, architects, and business stakeholders to deliver high-quality, scalable solutions.
• Strong communication skills and the ability to work both independently and collaboratively

Nice to have:

• Understanding of multithreading concepts and JVM process behavior as they relate to distributed systems
• Knowledge of data security, compliance, and governance best practices
• Familiarity with monitoring, alerting, and operational runbooks to support production-grade data pipelines

Interpersonal Skills:

• Proven experience collaborating with cross-functional teams in a dynamic business environment.
• Ability to effectively interface with and earn the respect of stakeholders at all organizational levels.
• Confident, energetic self-starter with excellent interpersonal skills.
• Demonstrates sound judgment, a sense of urgency, and a strong commitment to ethics, regulatory compliance, and business integrity.

Educational Requirements:

• Bachelor's or master's degree in computer science, information systems, engineering, or a related field candidates without these degrees should have a minimum of 4 years of professional experience.