Data Engineer

LS Power Development, LLC•New York, NY

18h

About The Position

This position is responsible for the design, maintenance, and reliability of the data infrastructure that supports our energy marketing and trading operation. You will the responsibility for the data layer behind a growing portfolio of internal business applications, ensuring that analysts, traders, and developers across the organization have timely access to clean, well-organized data. This is a hands-on, technical role embedded in a small, high-output software team. The ideal candidate is someone who thinks of data engineering not as an end in itself but as a means of solving real business problems. We value simplicity, clarity, and maintainability over architectural complexity.

Requirements

Have 5+ years of hands-on experience in data engineering, database administration, or a related data-intensive role.
Are proficient in SQL and have meaningful experience managing relational databases in production, whether SQL Server, PostgreSQL, or similar.
Have worked with a modern cloud data platform such as Microsoft Fabric, Databricks, Snowflake, or Azure Synapse, and understand the patterns of lakehouse and warehouse architectures.
Write Python comfortably for data pipeline development, automation, and scripting, and understand how to keep scripts clean, modular, and easy for others to maintain.
Have built data ingestion from real-world messy sources: APIs with pagination and rate limits, SFTP servers, email inboxes, inconsistently formatted files.
Believe that the best data infrastructure is the kind nobody has to think about because it just works, and you take pride in building systems that are boring in the best sense of the word.
Are a strong communicator who can translate between technical implementation and business requirements without losing fidelity in either direction.
Have a heavy bias to get to the end state through planning and action. Actions like performing the migration/refactor and dropping dead code and dead datasets.

Nice To Haves

Experience in the energy sector, particularly with energy marketing and trading data such as LMP pricing, SCADA, ISO market feeds, or commodity futures and derivatives.
Familiarity with energy market data vendors such as Bloomberg, ICE, Platts, NRG Stream, Databento, or similar.
Background in finance, gas, or commodities even if not specifically in power markets.
A demonstrated habit of building tools, automations, or personal projects at high volume — we value people who are prolific builders and problem solvers, not just people who have worked on one large system.
Active use of AI-assisted development tools and a thoughtful perspective on how to integrate them into a professional workflow responsibly.
Personal experience hosting, fine-tuning, or managing language models, or involvement in a technically ambitious personal project involving AI infrastructure.
An appreciation for software principles like KISS, DRY, and keeping complexity to a minimum — you would rather delete code than add it.

Responsibilities

Manage and extend a Microsoft Fabric environment including OLTP SQL Databases, lakehouses, warehouses, data pipelines, notebooks, and dataflows, ensuring reliable scheduled refreshes and data quality across workspaces.
Support data flows that underpin internal trading, settlements, and reporting applications.
Build and maintain data ingestion pipelines from a wide variety of sources: SFTP feeds, REST APIs, email attachments, flat files, and third-party energy market data vendors.
Own the operational reliability of data infrastructure: monitor pipeline health, troubleshoot failures, manage credentials and permissions, and handle workspace administration including item ownership transfers.
Develop applications that provide direct transparency into the underlying data that feeds complex analysis.
Manage ML training and inference pipelines that influence trading and plant management decisions.
Use master data management architectures alongside interactive applications to retain and reinforce critical business knowledge.