Job Description Summary

We are seeking a hands-on Data Systems Architect to design, build, and operate cloud-based data systems that support a Wind Energy Remote Operations Center (ROC). This role is deeply technical and execution-focused, responsible for developing and maintaining AWS-based data platforms using SQL and Python, while progressively enabling AI-driven analytics and automation to improve turbine performance, reliability, and operational decision-making.

Job Description

Job Title: Principal Data Systems Architect (AWS, SQL, Python – Wind Energy Operations)

Overview

We are seeking a hands-on Data Systems Architect to design, build, and operate cloud-based data systems that support a Wind Energy Remote Operations Center (ROC). This role is deeply technical and execution-focused, responsible for developing and maintaining AWS-based data platforms using SQL and Python, while progressively enabling AI-driven analytics and automation to improve turbine performance, reliability, and operational decision-making.

Renewable energy plays a critical role in reducing carbon emissions and supporting a more sustainable energy future. In this role, your work will directly contribute to improving the efficiency, reliability, and availability of wind energy assets—helping maximize clean energy generation while minimizing environmental impact. The data systems you design and operate will support real-world operational decisions that enable cleaner power at scale.

You will work directly with operational, engineering, analytics, and external stakeholders to turn high-volume, time-series, and event-driven data into reliable, actionable insights used by 24/7 operations staff.

Key Responsibilities

• Design, build, and maintain end-to-end data systems on AWS supporting real-time and batch wind operations data

• Develop hands-on SQL and Python pipelines to ingest, transform, and serve data from SCADA systems, EDGE systems, sensors, asset management tools, and operational applications

• Architect and optimize AWS services such as S3, RDS/Aurora, Redshift, Glue, Athena, Lambda, Step Functions, Kinesis, and related tooling

• Support Remote Operations Center (ROC) use cases including:

• • Real-time turbine monitoring, alerting and Troubleshooting

  • Performance, availability, and production reporting

  • Fault detection, root cause analysis, and event correlation

  • Fleet-level operational dashboards and analytics

• Design systems that can evolve to support AI-enabled use cases, such as:

• • Predictive maintenance and reliability modeling

  • Anomaly detection on time-series operational data

  • AI-assisted operational insights and decision support

• Partner closely with ROC operators, engineers, analysts, and customer stakeholders to understand operational workflows and translate them into robust technical solutions

• Own data quality, latency, reliability, and observability for operational data pipelines

• Tune system performance and manage cloud costs for high-volume, always-on workloads

• Contribute production code, perform peer reviews, and participate in operational support as needed

Required Qualifications

• 10+ years of hands-on experience building and operating data systems in production

• Strong experience designing and implementing AWS-based data architectures

• Advanced SQL skills for data modeling, time-series analysis, and performance optimization

• Strong Python experience for data ingestion, transformation, orchestration, and automation

• Experience working with real-time or near-real-time data systems

• Solid understanding of data lakes, data warehouses, and operational analytics platforms

Preferred Qualifications

• Experience supporting industrial, energy, or asset-intensive operations (wind, solar, utilities, manufacturing, oil & gas, etc.)

• Familiarity with SCADA, IoT, or high-frequency time-series data

• Customer-facing experience, including working directly with external customers, operators, or stakeholders to understand requirements, present solutions, and support production systems

• Interest in and aptitude for growing into AI/ML-enabled data systems, including supporting data pipelines used for predictive analytics, forecasting, or anomaly detection

• Familiarity with AWS AI/ML services (e.g., SageMaker, Bedrock) or exposure to ML concepts is a plus, but prior production ML experience is not required

• Experience with infrastructure as code (