Role: Python + Databricks consultant
Location: Houston, TX (remote possible for a top-tier expert)
Duration: 3 months
Interview: 2nd rounds virtual interview
What it's about:
The client needs a hands-on expert to design and build a Python + Databricks tool that models the operational and financial performance of Battery Energy Storage Systems (BESS), dispatch strategies (peak shaving, demand response, arbitrage, frequency regulation, voltage support), degradation modeling, dispatch optimization, and financial outputs (NPV/IRR/payback), delivered as an interactive Databricks App to support business development teams.
We're looking for a genuine hybrid profile: Python is the top priority, strong financial modeling/forecasting experience is a big plus, and BESS/energy market knowledge (ERCOT/PJM/CAISO, LMP, ancillary services) is a strong differentiator but not a hard requirement.
Role Overview
Our client, a major player in the energy sector, is seeking a senior independent consultant to design, build and deliver a Python-based software solution that models the operational and financial performance of Battery Energy Storage Systems (BESS) over a specified contract duration. The solution will support business development activities by providing robust analytical outputs to demonstrate project performance, viability and value to both external clients and internal stakeholders. The engagement combines energy storage domain expertise, U.S. power/energy markets knowledge, optimization, and hands-on software development (Python + Databricks).
Scope of Work
The consultant will be responsible for the end-to-end design, development and delivery of the solution, including:
- Development of a Python-based modeling engine for operational simulation and financial analysis
- Implementation of a Databricks App interface for data input, scenario configuration, and output visualization
- Design and implementation of data ingestion, transformation, validation, and processing pipelines
Required Expertise
- Strong Python engineering skills (pandas, numpy; optimization libraries such as Pyomo, PuLP or Gurobi a plus)
- Hands-on experience with Databricks (PySpark, Databricks Apps or similar interactive data-app frameworks)
- Solid understanding of U.S. wholesale power markets (LMP, ancillary services, capacity markets - ERCOT/PJM/CAISO experience valued)
- Battery storage domain knowledge: degradation modeling, SOC/SOH management, C-rates, dispatch optimization (rule-based, LP/MILP or hybrid)
- Financial modeling: NPV, IRR, discounted cash flow, payback analysis
- Data pipeline / ETL design for time-series and market data
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