Qode
Data Engineer
TLDR
This role focuses on enabling front-office, advisor, and trading operations through low-latency data pipelines and scalable architectures.
This role focuses on enabling front-office, advisor, and trading operations through low-latency data pipelines, scalable architectures, and governed data platforms. You will work closely with trading desks, portfolio management, and digital platforms to deliver reliable, compliant, and high-throughput data solutions.
Key Responsibilities
Trading 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 systems
Data 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 consumption
Performance, 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 systems
Governance, 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 requirements
Collaboration & 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 practices
Required 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 systems
Preferred 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
Qode is a technology-driven platform that transforms how recruiters and candidates connect by leveraging data and automation. Our solutions streamline the hiring process through machine learning, creating private talent pools and automating workflows, ultimately enhancing the quality of candidate evaluation and decision-making. With our no-code tools, we empower organizations to develop tailored recruitment strategies without needing extensive technical skills.
- Industry
- Internet Software & Services
Data Engineer