About this role
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.
• Daily meals provided – Enjoy free lunch at the office.
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.
• Daily meals provided – Enjoy free lunch at the office.
Tech stack
PostgreSQLMongoDBAWSAzureGCPBigQuery
About Vatic Labs
Vatic Labs is hiring for the finance data architect role. NewJob aggregates active openings directly from Vatic Labs's applicant tracking system, so this listing is current.
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