Senior Data Platform Engineer [Remote]

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Data Platform Engineer based in the United States.

This is a senior-level platform engineering role focused on building and evolving the data infrastructure that powers core product and business systems at scale. You will own the reliability, performance, and long-term architecture of data platforms that support everything from analytics and personalization to payments and operational reporting.
The role sits at the intersection of data engineering, DevOps, SRE, and backend systems, requiring both strong hands-on execution and strategic platform thinking.
You will help modernize legacy data systems into a scalable, observable, and well-governed platform that engineering teams across the organization can rely on.
A key part of your impact will be ensuring data pipelines and infrastructure are resilient, well-instrumented, and continuously improving.
You will collaborate closely with engineers, data scientists, and product stakeholders to understand needs and translate them into robust platform capabilities.
This role is ideal for someone who enjoys balancing operational ownership with long-term architectural evolution in a fast-moving engineering environment.

Accountabilities:

• 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.

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.
• Nice to have: experience with Kubernetes, data observability tools, ML infrastructure, or AI-assisted engineering workflows.
• Bonus: experience owning platform direction or working in environments without strict product management layers.

Benefits:

• Competitive salary range of $165,000 – $205,000 USD , depending on experience.
• Equity participation and long-term incentive opportunities.
• Comprehensive health coverage including medical, dental, and vision insurance.
• Fully remote, distributed-first work environment across the US and internationally.
• Unlimited PTO plus standard company holidays.
• Generous parental leave and family support benefits.
• Home office, co-working, internet, and professional development stipends.
• Mental health and wellness support programs.
• Annual learning and development budget to support career growth.
• Discounted subscription access to platform content and resources.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.