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

·         Minimum of 10 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