Senior Developer II — Enterprise Data Platform

Neuberger Berman•New York, NY

3d•$130,000 - $180,000•Hybrid

About The Position

Neuberger is looking for a Senior Developer II to help architect and scale the firm's enterprise data platform — a high-visibility, hands-on engineering role sitting at the intersection of AI, Data Science, and Enterprise Data Management. You'll be a key contributor to Neuberger's data-driven transformation — shaping platform strategy, influencing technical direction, and directly enabling research and data science outcomes. If you're a technically deep, highly motivated engineer who wants to work on meaningful problems at scale in financial services, this role was built for you.

Requirements

7+ years of hands-on platform or data engineering experience, with a demonstrable track record of owning and delivering production-grade systems.
Financial or investment management background is strongly preferred.
Demonstrated experience and proficiency across the modern data stack in data engineering and ELT development, including designing and building robust, scalable data pipelines that handle large volumes of both structured and unstructured data.
Proven hands-on experience with technologies such as Java, Kafka, Spark, Snowflake, Airflow, Databricks, Azure, dbt and OpenShift.
Proficiency with Python and python-based data science libraries (e.g., scikit-learn, pandas, NumPy, PyTorch, or TensorFlow) and the ability to collaborate effectively in Python-centric data science environments.
Hands-on experience with Apache Airflow or similar orchestration and scheduling tools.
Proficiency in cloud deployment models and platforms like AWS, Azure, or Google Cloud.
Strong communication skills, with the ability to engage effectively with both technical and non-technical stakeholders.
Highly collaborative approach with the ability to work in dynamic, fast-paced environments.
Ability to identify and solve complex problems, leveraging emerging technologies to drive innovation and operational efficiency.
Ability to work independently while fostering a collaborative team environment.
Effective at communicating technical concepts — including data science workflows — and strategic priorities to a wide range of audiences.
Highly driven and results-oriented, with a passion for delivering high-impact solutions at the intersection of data engineering and applied data science.

Nice To Haves

Bachelor’s degree is preferred, with a master’s or equivalent experience in a relevant field being a plus.

Responsibilities

Build and maintain advanced data engineering solutions – spanning data ingestion, storage, processing, and publication – with a focus on enabling modern AI and analytics workflows.
Contribute to the design, development, and deployment of the enterprise data platform, ensuring it meets the scalability, performance, and security needs of the business.
Implement and optimize cloud-based data platforms with a focus on leveraging tools like Snowflake, Databricks, and big data ecosystem technologies to drive data transformation and analytics for AI enablement.
Partner with senior platform leadership to align development initiatives with the firm’s strategic data management roadmap and enterprise architecture.
Evaluate and implement emerging technologies and tools to enhance the capabilities of the platform, ensuring the firm remains at the forefront of data innovation.
Contribute to data quality, observability, and monitoring frameworks that ensure platform reliability and trust in the data at scale.
Provide technical guidance and mentorship to junior engineers, helping elevate the broader team’s capabilities and engineering standards.