Mid-Level Data Engineer
About The Position
We’re looking for a Data Engineer to build, improve, and support the data pipelines and infrastructure that power our products and organization. You’ll work with SQL, Python, Spark/PySpark, Databricks, AWS, and Infrastructure as Code to develop reliable, scalable data solutions and help ensure the performance and quality of our production data environment. You’ll collaborate with engineers, data scientists, and teams across Crisis Text Line to translate data needs into thoughtful, maintainable solutions. We’re looking for someone with strong data engineering fundamentals and hands-on experience building and supporting production data pipelines. You don’t need experience with every technology in our environment—we value transferable experience, curiosity, and the ability to learn and solve problems collaboratively.
Requirements
- Approximately three to five years of professional data engineering, software engineering, or related experience, including meaningful responsibility for production data pipelines.
- Professional experience using SQL and Python to build, transform, and troubleshoot data.
- Experience building, maintaining, and supporting production data pipelines or ETL/ELT workflows.
- Experience with distributed data processing technologies such as Spark or PySpark.
- Familiarity with cloud-based environments such as AWS and modern data engineering practices.
- Experience testing, debugging, monitoring, and improving the reliability and performance of production data systems.
- The ability to independently complete well-defined engineering work, investigate problems, and clearly communicate technical decisions, risks, and tradeoffs.
- A collaborative approach to working with engineers, data scientists, and cross-functional partners, with a commitment to building secure and reliable data systems.
Nice To Haves
- Databricks or a comparable cloud-based data platform.
- AWS services and cloud-based data architecture.
- Terraform or another infrastructure-as-code tool.
- Lakehouse modeling such as medallion architecture and data warehousing.
- Datadog or comparable monitoring and observability tools.
- Data quality, automated testing, CI/CD, or deployment automation.
- Designing data systems for reliability, performance, scalability, and security.
- Supporting data used for analytics, reporting, or machine learning workloads.
- Claude or other AI-assistance code tools.
- Working in a mission-driven, regulated, safety-sensitive, or high-trust environment.
- Reliable High-Speed Internet Required: Must have a stable high-speed internet connection to support seamless remote collaboration, virtual meetings, online job tasks, etc.
Responsibilities
- Design, build, maintain, and improve reliable production data pipelines as part of our broader data and engineering environment.
- Develop and optimize data processing workflows using SQL, Python, Spark/PySpark, and Databricks.
- Partner with engineers, data scientists, and business teams to understand data needs and translate them into practical, maintainable solutions.
- Build and maintain integrations between data sources and our data infrastructure.
- Use Infrastructure as Code practices to support and improve our AWS data environment.
- Monitor pipeline health, data quality, and performance; troubleshoot issues and contribute to solutions when something isn’t working as expected.
- Automate repeatable processes that improve the reliability, efficiency, and maintainability of our data pipelines.
- Participate in shared production support and develop confidence diagnosing and resolving pipeline issues independently.
- Contribute to code reviews, technical documentation, and engineering standards that help the team build reliable and maintainable systems.
- Bring ideas, ask questions, and identify opportunities to improve our data tools, processes, and engineering practices over time.
Benefits
- Comprehensive medical, dental, and vision options that prioritize accessibility and financial peace of mind
- Employer-funded HSA contributions
- Generous PTO, sick time, and 19 paid holidays with a winter break
- 12 weeks of fully paid parental leave after 26 consecutive weeks of service
- Monthly internet and mental health stipends
- Annual Wellness Stipend
- Home office and professional development stipends
- 403(b) retirement plan with employer contribution
- Sabbatical after 3 years of service
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
