# Data Engineering Manager

**Company:** [Geneva Trading](https://hotfix.jobs/companies/geneva-trading)
**Location:** Chicago, IL
**Role:** Data Engineering
**Experience:** 7+ years
**Skills:** kdb+, q, Python, C++, Linux, Docker, fix, sbe, kernel-bypass networking, market data protocols
**Posted:** 2026-07-07

> Data Engineering Manager to own market data platforms and analytical data systems at a proprietary trading firm. Hands-on role managing a small team while writing production code, leading KDB+/Q time-series architecture, building low-latency pipelines, and evolving the platform for AI-driven consumers. Requires 7+ years data engineering experience with strong KDB+/Q and Python background.

## Job Description

## Key Responsibilities

**Market Data Pipeline Engineering**
- Own the market data pipeline from ingestion through normalization and near-real-time delivery. The data has to be correct first, and the system has to recover cleanly when something breaks.
- Integrating direct exchange feed capture alongside third-party vendor data
- Building and improving replay, recovery, and gap-detection capabilities
- Keeping market data correctly sequenced, validated, and available fast enough for downstream users
- Understanding when latency matters, when durability matters more, and how to make the right tradeoff

**Time-Series Architecture: KDB+/Q**
- Design, maintain, and improve the KDB+/Q platforms that hold our real-time and historical market data.
- Schema design, partitioning, and query-performance tuning
- Supporting real-time and historical analytics use cases
- Managing retention and data lifecycle policies
- Keeping the platform maintainable as data volumes and usage grow
- Debugging production HDB and tickerplant issues directly

**Data Distribution & Platform Integration**
- Deliver data reliably to downstream consumers through streaming, messaging, and platform integrations.
- Defining data contracts and schemas that other teams can depend on
- Supporting replayable and durable data flows where needed
- Working with downstream teams to understand how they actually consume the data
- Balancing real-time delivery needs with reliability and operational simplicity

**Tooling, Libraries & Supporting Systems**
- Build the internal tooling and shared libraries that make the data platform easier to operate and easier to use.
- Building validation, monitoring, replay, and analytics tools
- Owning supporting systems for reference data, configuration, and metadata
- Improving developer workflows around market data testing and troubleshooting
- Reducing repeated manual work through better tools and automation

**Technical Leadership & Production Ownership**
- Lead the team by staying close to the work.
- Writing production code
- Reviewing pull requests and technical designs
- Working directly with trading and research teams to understand their needs
- Debugging production issues during market hours when needed
- Setting expectations for quality, reliability, and maintainability
- Improving monitoring, alerting, and data-quality checks so problems are caught before the desk finds them

## Technology Stack
- KDB+ / Q
- Python
- C / C++
- Linux
- Docker
- Git / CI-CD
- Binary market data protocols
- Streaming / message bus platforms
- Kernel-bypass / high-performance networking
- Industry-standard messaging protocols (FIX, SBE)

## Required Qualifications
- At least 7 years of experience in data engineering, market data infrastructure, or a closely related area
- Current hands-on production coding experience
- At least 3 years leading engineers while staying technically involved
- Strong KDB+/Q experience, including complex Q, tick architecture, query tuning, and production HDB troubleshooting
- Strong production Python experience, including tested, packaged, maintainable systems-level code
- Experience building low-latency decoders for real exchange protocols
- Strong understanding of multicast, packet capture, sequencing, and gap detection
- Comfortable working in Linux and using tools such as perf, strace, tcpdump, and numactl
- Able to own production issues directly, not just route them to someone else

## Preferred Qualifications
- Background in high-frequency trading, market making, proprietary trading, or another latency-sensitive environment
- C or C++ experience for performance-critical decoder or capture components
- Experience with kernel-bypass or high-performance networking technologies
- Experience with streaming platforms used in real-time data pipelines
- Working knowledge of binary market data encoding standards

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