AWS Data Engineer
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What you'll do
- 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.
What they're looking for
- 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.
Nice to have
- 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
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
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.
Company
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