Senior Software Engineer, Market Data

Delinian•Sarasota, FL

About The Position

Ned Davis Research (NDR), an independent investment research company owned by Delinian Ltd, is seeking a senior software engineer to work across internally developed software supporting market data ingestion, transformation, validation, documentation, and serving. The role spans Java services and libraries, SQL Server-backed workflows, file-based processing, and vendor integrations, while also contributing to modernization of the platform. The engineer will need to understand complex legacy systems, improve them safely, and help shape the platform’s future. The position works with Java-based libraries, services, utilities, and web applications; SQL Server workflows and data structures; Linux file-system-driven pipelines; market data documentation and serving platforms; and batch jobs, loaders, updaters, validators, and scheduled workflows. It also involves shared framework code, formula engines and rule systems, web services, and test/support projects that protect business-critical data logic. Vendor integrations include Refinitiv, Bloomberg, Haver, S&P, MSCI, and other market data providers. The role is expected to help evolve the platform toward data lake-oriented ingestion and storage, improved documentation and serving, more modular and automated ingestion pipelines, stronger testing and validation, and interfaces with AI platforms as a source of market data. Potentially relevant platform components include Apache Polaris or similar catalog and governance tools, Apache Airflow or similar orchestration platforms, and OpenMetadata or similar data discovery, observation, and governance platforms. Success means making complex production changes safely, bringing clarity to difficult market-data problems, improving reliability and maintainability, advancing the platform toward modern data architecture, and becoming a trusted technical leader across the NDR Market Data ecosystem.

Requirements

Extensive software engineering experience, with competence expected of a very senior engineer.
Strong Java development background.
Experience in production systems involving databases and file-based workflows.
Familiarity with SQL Server or similar relational databases.
Experience with backend data pipelines, loaders, or integration platforms.
Strong debugging, system design, and problem-solving skills.
Ability to work effectively across multiple repositories and shared libraries.
Excellent communication and ownership.

Nice To Haves

Deep experience with market data platforms.
Strong background in timeseries data and membership-set or constituent data.
Familiarity with Refinitiv, Bloomberg, Haver, FactSet, Markit, MSCI, or similar vendor ecosystems.
Experience with data lake architectures.
Experience modernizing legacy Java or database-heavy systems.
Experience with formula engines, rule processing, or internal DSLs.
Experience supporting both internal tooling and commercial data products.
Experience with market data membership or constituent sets, vendor data normalization and survivorship, data history and revisions, point-in-time correctness, reference models, and derived datasets.
Experience with Apache Polaris or similar catalog and governance platforms, Apache Airflow or similar orchestration platforms, or OpenMetadata or similar data discovery, observation, and governance platforms.

Responsibilities

Lead development across Java services, libraries, and applications.
Improve data ingestion, validation, and serving workflows.
Work with SQL Server schemas and operational databases.
Integrate vendor feeds and normalize market and reference data.
Debug production issues across code, data, and infrastructure boundaries.
Refactor legacy systems safely.
Improve automated testing for parsing, calculations, and data correctness.
Help modernize platform architecture and technical practices.
Support market data ingestion and serving for client-facing processes.
Document key systems and processes.
Help evolve the platform toward data lake-oriented ingestion and storage, improved documentation and serving, modular and automated pipelines, stronger testing, and AI-platform interfaces for market data.