Data Engineer (UAE)

• Design, implement, and own end-to-end ETL/ELT pipelines (batch and streaming) from ingestion to feature delivery.


• Model financial datasets and define schemas, partitioning, indexing, and SLAs for analytical and real-time use cases.


• Operate and optimize OLTP/OLAP, search, and vector stores; tune performance, cost, and reliability.


• Build data quality checks, lineage, and observability; automate testing and deployment of pipelines.


• Collaborate with Quant/AI teams to productionize new data sources and features.

• Advanced SQL; strong experience with MySQL and PostgreSQL.


• Proficient with non-relational and vector databases: MongoDB, Elasticsearch, Chroma (or similar).


• Production experience with data layers on AWS / Azure / GCP (e.g., S3/GCS/ADLS, Redshift/BigQuery/Synapse, Glue/Dataproc/Data Factory).


• Have built ETL/ELT pipelines end-to-end (orchestrated, monitored, and supported in production).


• Familiar with financial data schemas and data modeling (tick/trade/quote, fundamentals, alternative data, vendor formats).

At Vatic, we’re serious about our work—but we also believe in balance, growth, and having fun along the way. Here’s what you can expect:

• Flat structure with direct executive exposure – Work closely with leadership and make an impact from day one.


• Comprehensive health benefits – Full health insurance coverage for employees and dependents.