The posting
ON.energy is setting the standard for large load interconnection. ON’s patented AI UPS™ is a medium-voltage UPS that serves as a firewall, protecting the data center from the grid, and the grid from the data center. With multiple gigawatts currently under construction, we are enabling grid-safe data centers.
Role Summary
ON.energy is building the power infrastructure that makes the AI era possible. Our systems are deployed across 2.5 GW of hyper-scale campuses, validated by top U.S. national labs, and certified for grid-safe operation by major utilities. You’ll be the fourth engineer on a growing data team, helping scale our AWS-based data lakehouse and working primarily with industrial data sources and high-volume time-series data. No prior experience in the energy sector is required, we’ll support you in learning the domain.
Key Responsibilities
- Build and maintain scalable ETL/ELT pipelines for batch and real-time processing, including high-frequency time-series ingestion.
- Evolve the Data Lakehouse — optimizing storage, performance, cost, and data consistency.
- Manage orchestration workflows with complex dependencies and error handling.
- Deliver production-ready, analytics-optimized datasets, engaging directly with end users to understand how they consume data.
- Implement data governance, security controls, and audit policies across the AWS ecosystem.
- Build monitoring, alerting, and data quality testing for platform reliability.
Key Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, or a closely related discipline.
- 3+ years of hands-on Data Engineering on AWS, with real exposure to modern data lakehouse architectures.
- English at B2 or above. Daily work with English-speaking teams and written documentation.
- Production experience with open table formats, preferably Apache Iceberg (table design, partitioning, schema evolution). Coming from Delta Lake or Hudi? We’ll support you in transitioning.
- Core AWS data services: Glue, Athena, Lambda, and S3.
- Designing and maintaining ETL/ELT pipelines for batch and streaming workloads.
- Python (PySpark / Python Shell) and advanced SQL (window functions, CTEs, execution plan tuning).
- Data modeling for analytical workloads in a lakehouse context — medallion architectures, incremental loads, deduplication, historical backfills.
- Infrastructure as Code: Terraform or CloudFormation.
Preferred Experience
Step Functions · Kinesis · Lake Formation · DynamoDB · custom ETL with boto3, pyiceberg, pyarrow · CI/CD for Glue or Lambda · time-series and IoT/telemetry data at scale
#LI-AD1
For US-based roles - What you’ll get:
- Competitive salary + annual performance-based bonus eligibility
- Medical, dental, and vision insurance
- 401(k) with company match
- Paid time off and company holidays
For Mexico-based roles - What you’ll get:
- Competitive salary + annual performance bonus eligibility
- Christmas Bonus (Aguinaldo): 30 days
- Major medical expenses and life insurance
- Paid time off and holidays (per local policy)
For all roles:
- Professional development and growth opportunities
- Opportunity to grow with a mission-driven team shaping the future of clean energy
- Equal Opportunity: ON.energy is committed to equal employment opportunity and to maintaining a work environment free of harassment, discrimination, or retaliation.
- Benefits vary by role and location and are subject to change.
Agency Notice: ON.energy does not accept unsolicited resumes from staffing agencies, search firms, or third-party recruiters. Resumes submitted without a fully executed Master Services Agreement (MSA) and a written request from an authorized member of our Talent Acquisition team will be considered the property of ON.energy. No placement fees or compensation will be paid for unsolicited candidate submissions.
