Job Description

We’re looking for a hands-on Data Engineer to build and scale the data foundation that powers research and trading. You’ll design schemas, pipelines, and storage layers across relational, NoSQL, and vector databases; productionize ETL/ELT on public clouds; and partner closely with researchers to model complex financial datasets.
What You’ll Do

• 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.

Required Qualifications

• 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.