7 часов назад
Software Engineer, Data Engineering
180 000 - 250 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Engineer, Data Engineering (Data Platforms): Designing and building data platform tools, pipelines, and orchestration frameworks for energy intelligence products with an accent on data quality, governance, and large-scale processing. Focus on developing reusable data libraries, supporting streaming and batch workloads, and scaling cloud-native systems for analytical and AI/ML workflows.
Location: United States (remote)
Base pay: $180,000–$250,000+ per year, excluding benefits and potential equity.
Company
is building an energy intelligence platform for the AI economy, combining real-time control of energy assets with visibility into energy portfolios.
What you will do
- Design, build, and maintain data platform tools, pipelines, and orchestration frameworks supporting multiple teams and products.
- Ensure data quality, contracts, integrity, access, governance, and federation across the data lifecycle.
- Develop shared libraries and reusable data tools for di data flows, sources, and sinks.
- Partner with Data Science and data-heavy teams on analytical and AI/ML workflows.
- Review code, maintain technical documentation, and promote test-driven software engineering practices.
- Evaluate system designs and drive implementation of scalable, high-quality solutions.
Requirements
- Advanced software development skills in Python, Rust, Java, Scala, or a similar data-oriented ecosystem.
- Deep understanding of databases, data lake and data warehouse architectures, and cloud-native data pipelines.
- Experience processing large, complex data in streaming and batch workloads across transactional and analytical systems.
- Strong commitment to software quality, delivery discipline, and contemporary engineering practices.
- Regular use of generative AI tools in day-to-day engineering work.
- Must be based in the United States.
Nice to have
- Senior-level software development experience or above and technical leadership in data engineering teams.
- Experience with Hadoop, Spark, Airflow, DBT, Dagster, Temporal, Trino, Iceberg, Postgres, BigQuery, S3, GCS, or similar technologies.
- Experience building event-driven architectures with Kafka, NATS, Pub/Sub, Kinesis, Flink, or Beam.
- Experience with managed data platforms, di data formats, AI/ML teams, MLflow, Ray, dashboards, or data visualizations.
Culture & Benefits
- Empathetic, humble, and respectful working environment.
- Emphasis on honesty, transparency, and effective communication.
- Flexible hours and unlimited paid time off.
- Medical, dental, and vision insurance, plus a 401(k).
- Competitive compensation, equity grant, and a di, inclusive workplace.
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