Senior Data Platform Engineer

Jobgether • United State
Remote
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AI Summary

Design and build scalable data systems, collaborate with cross-functional teams, and drive platform reliability and modernization.

Key Highlights
Own and evolve the data platform infrastructure
Partner with engineering and data stakeholders to translate platform needs
Develop and maintain Python-based tooling for pipelines and automation
Key Responsibilities
Own and evolve the data platform infrastructure supporting ingestion, transformation, orchestration, and observability across the organization
Build, maintain, and modernize core data systems that support product, analytics, and engineering workflows
Partner with engineering and data stakeholders to translate platform needs into scalable system designs
Technical Skills Required
Python Amazon Web Services SQL
Benefits & Perks
Fully remote-first environment
100% employer-covered healthcare
Generous parental leave and mental health support programs

Job Description


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

This role sits at the heart of a modern, high-impact data organization, responsible for building and evolving the infrastructure that powers critical product and business decisions at scale. You will work across ingestion, orchestration, observability, and transformation layers, ensuring data systems are reliable, performant, and easy to use for engineering and data science teams. The environment blends hands-on engineering with platform ownership, requiring someone who can balance operational stability with long-term architectural evolution. You will contribute directly to the systems that enable personalization, analytics, financial transactions, and content discovery experiences. This is a highly cross-functional role where collaboration with product, backend, and infrastructure teams is constant. It is ideal for someone who enjoys both solving immediate production issues and driving foundational platform improvements.

Accountabilities

Own and evolve the data platform infrastructure supporting ingestion, transformation, orchestration, and observability across the organization, ensuring it remains reliable, scalable, and well-documented.

  • Build, maintain, and modernize core data systems that support product, analytics, and engineering workflows
  • Drive platform reliability by improving monitoring, alerting, incident response, and reducing operational toil
  • Partner with engineering and data stakeholders to translate platform needs into scalable system designs
  • Contribute to long-term architectural direction, including modernization and migration of legacy systems
  • Develop and maintain Python-based tooling for pipelines, automation, and data quality enforcement
  • Apply DevOps and SRE principles to ensure uptime, performance, and operational excellence across the stack
  • Mentor engineers and help define best practices for platform reliability, documentation, and system design

Requirements

Experienced data platform or backend engineer with strong technical depth and the ability to operate across infrastructure, data engineering, and reliability domains.

  • 4-6+ years of experience in data engineering, backend engineering, DevOps, or SRE roles
  • Strong proficiency in Python, including building production-grade systems and tooling
  • Experience with data platforms and tools such as Snowflake, dbt, Spark, or similar ecosystems
  • Familiarity with cloud infrastructure (AWS preferred) and distributed systems concepts
  • Understanding of observability, monitoring, and production reliability practices
  • Ability to work effectively across legacy systems while driving incremental modernization
  • Strong systems thinking with the ability to balance short-term execution and long-term architecture
  • Collaborative mindset with strong communication skills and adaptability in ambiguous environments
  • Experience with Kubernetes, data observability tools, or ML infrastructure is a plus

Benefits

  • Fully remote-first environment with distributed teams across multiple regions
  • 100% employer-covered healthcare for employees and partial coverage for dependents
  • Generous parental leave and mental health support programs
  • Financial wellness resources and advisory support
  • Stipends for home office setup, co-working, internet, and professional development
  • Unlimited paid time off plus standard company holidays
  • Access to a discounted platform membership and product perks
  • Inclusive, mission-driven culture focused on learning, autonomy, and impact

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!

Why Apply Through Jobgether?

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.

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.


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