Senior Data Platform Engineer
New
Based in the United StatesFull-TimeSenior
Salary$165,000 – $205,000 USD
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Job Details
- Experience
- 4–6+ years
- Required Skills
- AWSPythonSnowflakeData engineeringSparkDevOpsdbt
Requirements
- 4–6+ years of experience in data engineering, backend engineering, DevOps, or SRE roles with strong exposure to data platforms or distributed systems.
- Strong proficiency in Python and experience building production-grade tooling or data pipeline systems.
- Experience working with data infrastructure technologies such as Snowflake, dbt, Spark, or similar modern data stack tools.
- Solid understanding of cloud infrastructure (preferably AWS) and familiarity with building and operating scalable systems.
- Experience with observability, monitoring, and reliability engineering practices in production environments.
- Ability to work across the stack, including data pipelines, backend services, and infrastructure automation.
- Strong systems thinking with the ability to diagnose issues, manage technical debt, and design long-term improvements.
- Comfortable working in ambiguous environments and independently driving technical solutions.
- Strong collaboration and communication skills, with a focus on building systems that support downstream engineering and product teams.
Responsibilities
- Build, maintain, and modernize the core data platform infrastructure supporting ingestion, transformation, orchestration, and analytics workflows across the organization.
- Own reliability and performance of data systems by improving observability, reducing operational toil, and proactively addressing system risks.
- Design and implement Python-based tooling for data pipelines, workflow orchestration, data quality checks, and infrastructure automation.
- Apply DevOps and SRE principles to ensure high availability, strong monitoring, effective alerting, and resilient deployment practices.
- Contribute to the evolution of platform architecture, including migration of legacy systems to modern, scalable infrastructure.
- Partner with engineering, product, and data teams to understand requirements and design data solutions that are reliable and easy to use.
- Improve system observability by enhancing logging, metrics, tracing, and alerting across data workflows.
- Review, optimize, and support data pipelines and infrastructure components to ensure efficiency and scalability.
- Mentor engineers and contribute to shared engineering standards around reliability, documentation, and platform best practices.
- Participate in shaping the long-term roadmap for the data platform, balancing short-term stability with long-term modernization.
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