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# Software Engineer, Data Engineering

- **Company:** Superhuman LLC
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $225,000.0 - $275,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Data Analysis, Batch Processing, Big Data, BigQuery, Cloud Computing, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Systems, Software Design Patterns, Distributed Systems, Python (Programming Language), Machine Learning, SQL Databases, Workflow Management Systems, Data Storage Technologies, Snowflake, Apache Spark, Backend, Data Lakes, Data Analytics, Apache Kafka, Build Tools, Terraform, Data Pipelines, Amazon Redshift, Programming Languages
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_1e13f5924c3b7262fd8a5fe867d1909a

## About the Role

* Brings at least 10 years of experience in large-scale distributed computing systems, with expertise in both data engineering and data modeling.
 * Has 5+ years of experience managing live production environments, including high-load systems or data-intensive workflows with a focus on uptime and reliability.
 * Expert in SQL and proficient in technologies like Spark, Kafka, Terraform, and in at least one programming language commonly used for data engineering (e.g., Python, Scala, or Java).
 * Strong knowledge of ETL/ELT design patterns, orchestration tools (e.g., Airflow, dbt, Dagster), and data quality frameworks.
 * Ability to design scalable, secure, and maintainable data models and architectures, and understanding of data governance, privacy regulations (GDPR/CCPA).
 * Hands-on experience with modern data storage technologies (e.g., Delta Lake, Snowflake, BigQuery, Redshift).
 * Is a strategic thinker, able to evaluate whether to build internally or leverage third-party solutions, ensuring the right balance between speed, scalability, and long-term viability.
 * Is an excellent communicator and collaborator, able to work across diverse teams and stakeholders, translates business needs into robust data solutions, and ensures alignment on technical goals.
 * Has a demonstrated ability to work independently with minimal guidance, proactively manages tasks and priorities across multiple projects, analyzes and executes work efficiently, collaborates effectively with cross-functional teams, and thrives in fast-paced, results-driven environments.

## Description

As a Software Engineer on the Data Platform team, you will shape the architecture and technical strategy of our data platform, ensuring scalability, security, and efficiency across data engineering systems. You will design and lead the implementation of robust, scalable, and reliable systems that handle large volumes of data, empowering both product features and data-driven decision-making across the company. Your work will span areas such as real-time & ETL data pipelines, cloud infrastructure, data lakes, and back-end services., This role requires you to collaborate with cross-functional teams, including back-end engineers, Analytics engineering, Data Science engineering, and machine learning teams, to drive initiatives that support various business outcomes. As a senior IC, you will also mentor engineers and help set the strategic direction for the platform., * Architect and lead the development of large-scale systems for data pipelines, data lakes that handle billions of daily events.

 * Design and implement solutions that ensure data is available, secure, and scalable across the platform, enabling real-time and batch processing.
 * Make high-level architectural decisions about system design, technology choices, and platform evolution, ensuring scalability and long-term sustainability.
 * Collaborate with key stakeholders, such as product teams, data engineers, back-end developers, and ML engineers, to build tools & frameworks that power analytics, product features, and data-driven workflows.
 * Work with business stakeholders such as Analytics Engineering and Data Science teams to build high-impact data products enabling business-critical features, research, and experimentation with a focus on efficiency and alignment.
 * Collaborate with Leadership in devising the charter and technical roadmaps.
 * Mentor engineers across back-end infrastructure and data engineering disciplines, fostering a culture of collaboration and technical excellence.