Profile 1: Data Platform Engineer ( Dubai)
Task: Design, build, integrate and operate enterprise data and AI platforms and tooling (Confluent, Databricks, dbt, OpenMetadata).
Expertise:
CDC replication and event streaming (Confluent, Kafka)
Data lake architecture (Databricks, Delta Lake, Unity Catalog)
Metadata management (catalog, lineage, data quality, context layer)
Data orchestration and engineering automation (Airflow, Dagster, dbt)
Platform engineering and DevOps (Kubernetes, Docker, CI/CD, Infrastructure as Code, monitoring)
Data protection and security (PII handling, masking, access controls, data policies)
Platform observability, incident response and operational support
Performance optimization, workload management and cost monitoring
Expected outcomes:
Reliable, scalable and secure data and AI platform services
Self-service capabilities for engineering, analytics and AI teams
Well-governed metadata, lineage and context management
High platform availability, performance and operational excellence
Productive and cost-effective platform usage




Banking, regulated-industry or large-enterprise experience preferred. Experience with both contemporary and traditional data platforms (e.g., Databricks, Oracle, Informatica) is appreciated.
Must have: Demonstrated use of AI-assisted development, context layers and agentic data-related workflows.

Profile 2: Data Engineer (Dubai)
Task: Build, operate and optimize data ingestion, processing and transformation pipelines that deliver trusted, business-ready data products.
Expertise:
Data modeling (Medallion Architecture, Data Mesh, Data Vault)
Data transformation frameworks (dbt, Databricks Declarative Pipelines)
Python and SQL development
Data quality engineering (Soda, Outstanding Expectations, dbt tests, Databricks quality frameworks)
Data pipeline design, optimization and troubleshooting
Business and product understanding
Analytical mindset and problem-solving
Ability to engag

📌 Data Platform Engineer Bengaluru
🏢 Anveshna Technologies
📍 Bengaluru