Principal Integration Engineer - Trade Data Warehouse

U.S. Bank • Chicago, IL

2d • $143,905 - $169,300 • Hybrid

About The Position

We are seeking an experienced Data Modeler, Designer, and Warehouse Engineer to lead data workstreams for a large-scale technology integration and transformation program within our Capital Markets and Electronic Trading organization. The candidate is a seasoned data engineering leader with strong technical, influential, and strategic abilities to help drive the success of the Electronic Trading Data Strategy. The ideal candidate will bring deep expertise in data and cloud technologies and lead a high-performing team of data engineers and architects responsible for the technical design, architecture, and engineering of data backends and warehouses for large, distributed trading systems. Additionally, the team will be responsible for building ETL workflows that move pre-and-post trade data between various back-office systems for settlement, market and counterparty risk analysis, and finance general ledger. What does it take to succeed in this role? You love working with data at high throughput and low latency. You are comfortable rolling up your sleeves and diving into the details while also able to articulate strategy and design (both high and low-level) to appropriate audience. You possess a unique blend of technical proficiency, superior leadership and communication skills, and a visionary approach to data platforms evolution and transformation. You foster a culture of innovation and high-performance.

Requirements

• Bachelor's degree, or equivalent work experience
• Ten or more years of relevant experience
• Strong skillset with SQL and able to model and design a RDMS for low latency, high throughput electronic trading backends.
• Proficiency with respect to cloud concepts such as RBAC, cloud blueprints and IaC tools such as terraform.
• Experience implementing and working with cloud data platform solutions such as Amazon Redshift, Snowflake, Data Bricks.
• Experience in Data Processing technologies such as Spark, Flink
• Data Security and Privacy: Understanding of data security principles, encryption techniques, and privacy regulations (e.g., GDPR, CCPA) to ensure data compliance.
• Deep understanding of Reference Data and Security Master concepts
• Deep understanding of Transactional Trade data
• Understanding of electronic trading market structure across one or more asset classes, such as fixed income, equities, equity options, commodities, or FX.
• Experience in Securities Data Modeling
• Working knowledge of market data, including aggregated and consolidated data, as well as montage books.
• Experience managing time series data.
• Understanding of post-trade feed flows, including settlement calculations.
• Build and run processes for the data backends using such technologies as public cloud infrastructure on AWS, Kafka, Message Queues, in-memory data grids like Coherence or Hazelcast, and databases (Postgres, SQL Server).
• Strong experience working with SQL and databases engines/warehouses such as PostgreSQL, SQL Server, Snowflake, Redshift, and Databricks.
• Experience building ETL with SSIS on SQL Server and/or ETL on PostgreSQL with Python/Pandas.
• Experience with stream processing pipelines using Kafka and Spark on Databricks, Snowflake, and Redshift; or experience with Stream processing using RabbitMQ streams to PostgreSQL output sink.
• Proficiency in Linux scripting, troubleshooting, and host tuning.
• Exposure to third-generation programming languages such as Java, .NET, and Python.
• Strong proclivity for test automation and DevOps practices
• General understanding of application frameworks like Spring (Java), Django (Python); package managers like Mavan (Java), npm (JavaScript) and nuget (.Net)
• Practical experience with Docker and Kubernetes.

Nice To Haves

• Experience in building large-scale data backends and warehouses for electronic trading platforms in trading desks for equities, fixed income, or derivative instruments.
• Advanced understanding of data warehouse, data lake, data lakehouse, and medallion architecture.
• Experience implementing self-service business intelligence solutions using tools such as Tableau and Power BI.
• Knowledge of data science, machine learning, and natural language processing concepts, with experience shaping data to support those needs.
• Understanding of Gen AI concepts and their applicability to pertinent use cases across various domains preferably electronic trading.

Responsibilities

• Lead data workstreams for a large-scale technology integration and transformation program within Capital Markets and Electronic Trading.
• Drive the success of the Electronic Trading Data Strategy.
• Lead a high-performing team of data engineers and architects responsible for the technical design, architecture, and engineering of data backends and warehouses for large, distributed trading systems.
• Build ETL workflows that move pre-and-post trade data between various back-office systems for settlement, market and counterparty risk analysis, and finance general ledger.
• Work with data at high throughput and low latency.
• Articulate strategy and design (both high and low-level) to appropriate audience.
• Foster a culture of innovation and high-performance.

Benefits

• Healthcare (medical, dental, vision)
• Basic term and optional term life insurance
• Short-term and long-term disability
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation (from two to five weeks depending on salary grade and tenure)
• Up to 11 paid holiday opportunities
• Adoption assistance
• Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: Associate degree