Senior Data Engineer

• Design, develop, and maintain scalable data pipelines and data solutions using Databricks and PySpark.
• Build and optimize ETL/ELT solutions for batch and near real-time data processing.
• Design and maintain enterprise Data Warehouse and Lakehouse solutions, including Delta Lake and Delta Tables.
• Develop dimensional data models using Fact/Dimension tables, Star Schema, Snowflake Schema, and SCD Type 1 & 2.
• Implement and maintain data governance and security using Unity Catalog, RBAC, ABAC, data lineage, auditing, and fine-grained access controls.
• Configure and manage Delta Sharing for secure internal and external data collaboration.
• Support Databricks Genie and Genie Spaces adoption and administration.
• Perform PySpark, SQL, Data Warehouse and Lakehouse performance tuning, including query, cluster and workload optimization.
• Develop and maintain CI/CD pipelines and automate deployment, testing and release processes using GitHub, GitHub Actions or equivalent tools.
• Collaborate with business users, data analysts, architects and technology teams to translate business requirements into scalable data solutions.
• Provide technical guidance and mentorship to junior team members where required.
• Continuously improve data platform performance, scalability, security, governance and cost efficiency.
  

Job Requirements:

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science or a related field.
• 5 years and aboveof experience in Data Engineering, Data Warehousing or Big Data technologies.
• Strong hands-on experience with Databricks, Azure Databricks, PySpark, Delta Lake, Delta Tables and Databricks Workflows.
• Strong knowledge of Unity Catalog, RBAC, ABAC, Delta Sharing, data governance and data security.
• Experience with Databricks Genie / Genie Spaces is preferred.
• Strong SQL skills with experience in query and data warehouse performance optimization.
• Solid experience in Data Warehouse architecture, Lakehouse architecture and Medallion design patterns.
• Strong knowledge of dimensional data modelling, including Fact/Dimension tables, Star Schema, Snowflake Schema and SCD.
• Experience with GitHub, Git-based workflows and CI/CD, preferably using GitHub Actions.
• Experience with at least one major cloud platform (Azure, AWS or GCP).
• Knowledge of Infrastructure-as-Code, preferably Terraform, data observability and monitoring is an advantage.
• Databricks certification is an added advantage.
• Strong analytical, problem-solving and troubleshooting skills.
• Good communication and stakeholder management skills, with the ability to work independently and across business and technical teams.