Analytics Engineer

Status: Available

Posting Date: 01/31/2025

Location: Houston, TX

Full Time: Yes

Part Time: No

Salary: $90,000.00 - 130,000.00

Type: DH

Description:

Education: Bachelor’s degree in finance, economics, or other related field

Experience: 2+ years of experience in the retail energy space in quantitative roles such as portfolio management analytics, structuring, or advanced financial modeling. 4+ years of experience in Python, including relevant data science tools such as pandas, numpy, sklearn. Experience with Big Data Frameworks and Distributed computing tools (Spark, PySpark, HDFS, MapReduce, Hive, Databricks, etc.) and building/deploying cloud applications. Strong software engineering background, including experience with data modeling, algorithms, and software quality processes (e.g., CI/CD tools, code reviews, testing & deployment automation, etc.). Experience in developing data products with large data sets and complex transformations that scale well in a distributed computing environment. Experience developing and analyzing P&L diagnostic tools, Mark-To-Market engines. Experience in retail costing and financial modeling of tariffs in deregulated electricity markets.

Job Categories: Information Technology

Responsibilities:

• Design and build software solutions to solve and generate value for business problems.
• Work with the commercial team on developing customer analytics data products for decision-making and optimizing customer P&L.
• Take ownership of the in-house ETRM (Energy Trading and Risk Management) and Load Valuation engine and become the subject matter expert for all valuations and reporting.
• Work with Portfolio Management and Finance teams on scoping and developing new modules and updates to our systems.
• Write high-quality, testable, maintainable production code.
• Develop automated, testable, and scalable solutions and data products.
• Develop automated data validation solutions for all inputs into the valuation engine.
• Develop and automate the demand response reporting and performance tracking data products.
• Work with Software and Data Engineering teams on improving our DevOps and CICD workstreams.
• Design and develop P&L diagnostics as well as a reporting layer for valuation outputs.
• Work with Engineering, Data Engineering, Credit, and Finance teams to seamlessly connect the valuation/financial systems to other systems.
• Lead the technical needs of ETRM implementation and work with Portfolio Management and Finance teams to design and develop upstream and downstream processes.
• Take ownership and lead the development of various projects and initiatives throughout the organization, working with the product team.
• Be a culture-setter, creating a collegial and supportive environment where teammates can develop as professionals and do great work.

Skills:

• Proficiency in Python, including relevant data science libraries such as pandas, numpy, sklearn.
• Strong software engineering skills, including data modeling, algorithms, and software quality processes.
• Familiarity with Big Data frameworks and distributed computing tools (Spark, PySpark, HDFS, MapReduce, Hive, Databricks).
• Experience with cloud application development and deployment.
• Strong analytical and problem-solving skills, particularly in the context of large datasets and complex data transformations.
• Ability to handle big data and design advanced solutions for large datasets.
• Ability to translate complex business concepts into production-quality code.
• Experience developing P&L diagnostic tools and Mark-To-Market engines.
• Strong communication skills to present complex data products and models to various stakeholders.
• Ability to develop strong working relationships with internal stakeholders, including credit, finance, data engineering, and software engineering teams.
• Experience developing BI reports using Power BI, Looker, or similar tools.

Requirements:

• 2+ years of experience in retail energy, specifically in quantitative roles such as portfolio management analytics, structuring, or financial modeling.
• 4+ years of experience in Python, with knowledge of data science tools (pandas, numpy, sklearn).
• Experience with Big Data Frameworks and Distributed computing tools (Spark, PySpark, HDFS, MapReduce, Hive, Databricks, etc.).
• Strong background in software engineering, data modeling, algorithms, and software quality processes.
• Experience developing and analyzing P&L diagnostic tools and Mark-To-Market engines.
• Familiarity with retail and wholesale energy markets, regulations, market design, and risks.
• Experience with financial modeling of tariffs in deregulated electricity markets.
• Ability to design and develop automated solutions, data products, and reporting layers.
• Strong ability to communicate technical concepts and systems to a broad range of stakeholders.
• Ability to work across multiple teams, including Engineering, Data Engineering, Finance, and Credit teams.
• Bachelor’s degree in finance, economics, or another quantitative discipline.
• Databricks experience is a plus.