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Software Engineer - Low Latency / Distributed Systems
Tier-1 Investment Bank, Dublin (Hybrid) - Contract

Leading investment bank's Dublin technology hub is expanding its high-frequency trading infrastructure team. This is deep, hard engineering - the systems you build execute trades in microseconds, and every millisecond you shave off is measurable P&L. Not a CRUD shop, not a maintenance role.

What you'll work on:

Low-latency, high-throughput distributed systems processing millions of market events per secondPerformance-critical execution paths in C++/Java/Rust - kernel bypass, lock-free data structures, zero-copy designMarket data ingestion, order routing, and risk systems operating at exchange speedDirect collaboration with quant developers and trading desks Profiling and tuning at the OS/network/hardware boundary - NUMA awareness, CPU pinning, kernel bypass networking (DPDK/Solarflare-style stacks)

What we're looking for:

Strong CS fundamentals - concurrency, memory management, networking internals, cache-aware designProduction experience in C++, Java, or Rust in a genuinely performance-sensitive environmentExposure to FIX protocol, market data feeds, or exchange connectivity is a strong plusComfortable working close to the metal - this isn't abstraction-layer engineeringFintech/trading background not mandatory - elite backend engineers from adjacent high-scale, low-latency domains (ad-tech real-time bidding, gaming infra, telco) will be seriously considered

Team & setup:

Small, senior engineering pod embedded within the trading technology groupHybrid - Dublin office, with onsite time expected around trading hours/desk collaborationContract engagement, initial term with strong likelihood of extension given desk growth plans

GCS is acting as an Employment Business in relation to this vacancy.

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The Team

The team sits within network technology organisation, building advanced data platforms that support digital twin capabilities across the access network. The group combines network design data, telemetry, mapping technologies, and large-scale engineering systems to improve troubleshooting, planning, operational efficiency, and competitive market analysis.

The team develops highly scalable platforms that ingest and process complex operational data, expose intelligence through APIs, and enable smarter decision-making across the business.

This is a technically strong team solving real-world infrastructure challenges using modern software engineering and data technologies.

ResponsibilitiesDesign, build, and maintain scalable ETL / ELT pipelines processing large enterprise datasets.Develop robust data products using Databricks, Spark, and cloud-based data platforms.Build configurable ingestion frameworks and multi-environment deployment pipelines.Engineer APIs that expose network intelligence products to internal teams and systems.Work with complex relational, structured, and semi-structured datasets representing network assets, telemetry, and operational events.Improve data quality, exception handling, observability, and pipeline resilience across multiple upstream data sources.Write production-grade software with strong engineering standards, testing, and automation.Collaborate with GIS, network engineering, and operational teams to solve business-critical problems.Support the evolution of digital twin and next-generation network intelligence platforms.Skills & ExperienceRequiredStrong software engineering background (Python preferred).Experience building production systems and scalable backend applications.ETL / ELT pipeline engineering experience.Experience with Spark, Databricks, or similar distributed data platforms.API development experience (REST / backend services).Strong SQL and data modelling skills.Experience handling large, imperfect enterprise datasets.Strong problem-solving skills and ability to work with complex systems.Experience with Airflow, AWS EMR, Snowflake, or similar modern data tools.GIS / geospatial data experience.Telecom, utilities, infrastructure, or network data experience.CI/CD and DevOps engineering practices.Experience building internal data products or platform services.Ideal Candidate

A strong software engineer with an interest in data engineering, or a data engineer with excellent coding discipline. Candidates with transferable adjacent skills are highly valued over exact tool matching alone. Someone who can build scalable systems, work through messy data challenges, and thrive in a complex enterprise environment.

GCS is acting as an Employment Business in relation to this vacancy.

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Senior Software Engineer / Data Platform Engineer (Databricks, Graph, APIs)

Location: Philadelphia, PA

The team sits within the network technology organisation and is responsible for building advanced data platforms that support digital twin capabilities across the access network. The group combines network design data, telemetry, mapping technologies, and graph intelligence to improve troubleshooting, planning, operational efficiency, and market competitiveness.

The team works on highly scalable engineering products including large data pipelines, graph databases, APIs, and mapping platforms. Their work enables smarter network decisions, faster fault resolution, and better use of operational resources.

This is a technically strong team focused on solving complex real-world problems using modern engineering and data technologies.

Responsibilities

Design, build, and maintain scalable ETL / ELT pipelines processing large enterprise datasets.Develop robust data products within Databricks and Spark environments.Build configurable ingestion frameworks and multi-environment deployment pipelines.Engineer APIs that expose network intelligence products to internal users and systems.Work with graph databases such as Neo4j to model relationships across network assets, devices, and telemetry.Improve data quality, exception handling, and pipeline resilience across multiple data sources.Write production-grade software with strong engineering standards, testing, and automation.Collaborate with technical teams to translate complex operational problems into scalable engineering solutions.Help evolve digital twin and next-generation network intelligence platforms.

Skills & Experience

Required

Strong software engineering background (Python)Neo4j graph database experienceExperience building production systems and scalable backend applications.ETL / ELT pipeline engineering experience.Experience with Spark, Databricks, or similar distributed data platforms.API development experience (REST / backend services).Strong problem-solving skills and ability to work with complex data.Experience with Airflow, AWS EMR, or similar orchestration/data tools.Telecom, infrastructure, or network data experience.CI/CD and DevOps engineering practices.Experience handling large, imperfect enterprise datasets.

Ideal Candidate

A strong software engineer with an interest in data engineering, or a data engineer with excellent coding discipline. Candidates with transferable adjacent skills are highly valued over exact tool matching alone.

GCS is acting as an Employment Business in relation to this vacancy.

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