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

- Efficient and cost-effective platform usage

- Banking, regulated-industry or large-enterprise experience preferred.

Experience with both modern 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, Great Expectations, dbt tests, Databricks quality frameworks)

- Data pipeline design, optimization and troubleshooting

- Business and product understanding

- Analytical mindset and problem-solving

- Ability to engage effectively with data consumers including analysts, data scientists and business stakeholders

- Expected outcomes:

- Reliable and maintainable ingestion and transformation pipelines

- High-quality, trusted and well-documented datasets

- Consistent and scalable data models aligned with business requirements

- Strong adoption of data products by business and analytics teams

- Effective monitoring and resolution of data quality issues

- Banking, regulated-industry or large-enterprise experience preferred.

Experience with both up-to-date 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.

Pay: ₹1,000,000.00 - ₹2,500,000.00 per year

Application Question(s)

- This Position is for Dubai, you are OK to relocate?

Experience

- Data Platform : 10 years (Required)

Willingness to travel

- 100% (Required)

Work Location: Hybrid remote in Bangalore City, Bengaluru, Karnataka

📌 Data Platform Engineer (Bengaluru)
🏢 Anveshna Technologies
📍 Bengaluru