California, CA10 days ago
Key ResponsibilitiesTrading Data Platform Engineering· Design and build real-time and batch data pipelines supporting trading workflows (orders, executions, positions, market data)· Develop low-latency data processing systems for near real-time decisioning· Build scalable data architectures for high-volume transaction data· Enable event-driven architectures using streaming platforms (Kafka, Kinesis)Wealth Management & Trading Integration· Integrate with trading platforms (OMS/EMS), portfolio systems, and advisor platforms· Support use cases such as:· Trade lifecycle tracking (order execution settlement)· Portfolio performance and analytics· Advisor dashboards and client reporting· Ensure data consistency across front-, middle-, and back-office systemsData Engineering & Architecture· Build and manage data lakes / lakehouse architectures (Delta Lake, Iceberg, etc.)· Develop ETL/ELT pipelines using modern frameworks· Design data models optimized for trading and analytics workloads· Implement API-driven data access layers for downstream consumptionPerformance, Scalability & Reliability· Optimize pipelines for low latency, high throughput, and fault tolerance· Implement data quality, reconciliation, and observability frameworks· Ensure high availability and disaster recovery for critical trading data systemsGovernance, Risk & Compliance· Implement data governance, lineage, and auditability· Ensure compliance with regulatory requirements (SEC, FINRA, etc.)· Enable data security, entitlements, and access controls· Support trade surveillance and reporting requirementsCollaboration & Delivery· Partner with trading desks, product teams, and architects to translate requirements into scalable data solutions· Work closely with AI/analytics teams to enable downstream insights and models· Mentor junior engineers and contribute to data engineering best practicesRequired Qualifications· 7–12+ years of experience in data engineering or backend engineering· Strong expertise in:· Python / Scala / Java· SQL and distributed data processing (Spark, Flink, etc.)· Hands-on experience with:· Streaming platforms (Kafka, Kinesis, Pulsar)· Data lake / warehouse technologies (Snowflake, Databricks, Redshift)· Experience building real-time or near real-time data pipelines· Strong understanding of data modeling and large-scale distributed systemsPreferred Qualifications· Experience in Wealth Management or Capital Markets trading systems· Familiarity with OMS/EMS platforms (e.g., Charles River Development, Aladdin, FIS)· Knowledge of market data (equities, fixed income, derivatives) and trade lifecycle / post-trade processing· Experience with cloud-native data platforms (AWS, Azure, GCP)· Exposure to real-time analytics and risk systems This role focuses on enabling front-office, advisor, and trading operations through low-latency data pipelines, scalable architectures, and governed data platforms.