·      Bachelor’s degree in Computer Science, Engineering, or a related field

·      Minimum of 5 years’ programming experience which includes a minimum of one year working with big data platform, experience in data engineering domain, Python, SQL, and cloud platforms such as Azure

·      Familiarity with the relevant systems, tools, languages and business domain which includes: Data lakehouse principles, relational and Kimball data models required

·      Experience with CI/CD pipelines and version control tools required

·      Knowledge of data visualization tools and BI platforms preferred

·      Certification in Databricks or relevant cloud platforms preferred

·      Design, build, and maintain scalable data pipelines on Databricks (using Spark, Delta Lake, etc.)

·      Write clean, efficient and maintainable PySpark or SQL code for data transformation

·      Design robust data models for analytics and reporting

·      Ensure data quality, consistency, and governance

·      Handle batch and streaming data workflows

·      Provide architectural guidance and support in platform usage

·      Drive best practices in data engineering across the team

·      Monitor and optimize performance of Spark jobs and cluster usage

·      Ensure compliance with security and data privacy standards

·      Ability to analyze large datasets and identify patterns, trends, and anomalies

·      Identify and troubleshoot issues in data pipelines, workflows, or infrastructure

·      Ensure data accuracy, integrity, and security during processing and transformation

·      Manage multiple tasks and deadlines, such as development, testing, and deployment

·      Translate technical concepts into actional insights for stakeholders

·      Excellent problem-solving and debugging skills

·      Strong communication and stakeholder collaboration abilities

·      Ability to lead initiative and mentor junior team members