Senior Data Platform Engineer

1Password2 months ago

Location

Remote (United States | Canada)

Workplace

Remote

Type

Full Time

Salary

USD 152,000 – 197,500

Level

Senior

Role

Data Engineer

Posted

May 22, 2026

Full TimeRemoteSenior

The role

Summary

Senior Data Platform Engineer at 1Password designing and operating a streaming-first, domain-oriented data platform serving near real-time analytics across Fortune 100 enterprises. This high-impact role combines infrastructure architecture, data governance, and platform engineering to enable self-serve access for analysts, engineers, AI systems, and business users, requiring 7+ years of experience with distributed systems, cloud platforms, and modern data technologies.

What you'll do

Design & Operate Streaming Data Platform: Architect, build, and maintain a streaming-first data platform powered by Apache Kafka, Protobuf, and Apache Iceberg, ensuring near real-time data availability across the organization with sub-second latencies for mission-critical data flows

Build Hybrid Data Architecture: Engineer and operate a hybrid Databricks and Snowflake infrastructure leveraging Databricks for data engineering, streaming processing, and AI/ML workloads while utilizing Snowflake as the governed serving layer for analytics, business intelligence, and reporting

Own Unified Storage Layer: Implement and maintain a unified storage layer using Apache Iceberg that ensures all data consumers operate on a consistent, governed, and well-documented data foundation with proper schema evolution and data quality guarantees

Champion Platform Standards & Best Practices: Establish and evangelize data platform standards, tooling, patterns, and best practices across the data organization including schema governance, data quality frameworks, and infrastructure standards

Enable Self-Serve Data Access: Build paved paths, documentation, and tooling that enable analysts, engineers, AI systems, and business users to independently access, understand, and leverage high-quality data for their respective needs

Lead Technical Initiatives: Identify and drive high-impact technical initiatives that transform the data platform, including source-owned domain orientation, real-time capabilities, and data product governance models

Mentor & Support Data Engineers: Lead through technical contribution while actively mentoring junior and mid-level data platform engineers, fostering a culture of continuous learning, code quality, and operational excellence

Implement Data Governance Framework: Design and enforce comprehensive schema governance, data quality monitoring, data lineage tracking, and data lifecycle management policies ensuring compliance and data trustworthiness

Optimize Performance & Cost: Continuously optimize data platform performance, query latency, compute utilization, and cloud spending across Databricks and Snowflake without compromising data availability or quality

Cross-Functional Collaboration: Work closely with engineering teams, product managers, analytics, and business stakeholders to translate data requirements into scalable platform capabilities and prioritize critical needs

What we look for

Technical

Streaming Architecture DesignExpert-level ability to design streaming-first architectures with event-driven data pipelines, schema governance, and near real-time data availability

Data Platform ArchitectureProficiency in building medallion-style architectures with bronze/silver/gold layers, unified storage implementations, and governed data serving layers

Distributed Systems EngineeringDeep understanding of scaling principles, data replication strategies, consistency models, fault tolerance, and high-availability system design

Schema Governance & Data QualityExpertise implementing schema registries, data validation frameworks, quality monitoring, alerting, and data lifecycle management policies

Cloud Infrastructure & ComputeAdvanced proficiency with AWS EC2, ECS, EKS, networking, storage services, and GCP equivalents for distributed data workloads

Infrastructure AutomationExpert-level ability to code infrastructure using Terraform and Ansible, implementing GitOps, configuration management, and repeatable deployment patterns

Secure Systems DesignStrong security practices including IAM implementation, least privilege access controls, encryption at rest and in transit, and compliance frameworks

Observability & MonitoringExpertise implementing comprehensive monitoring, logging, and alerting using Prometheus, Grafana, Datadog, and custom instrumentation

Large-Scale Data ProcessingHands-on experience building applications leveraging distributed processing frameworks, handling petabyte-scale datasets, and optimizing query performance

Education

Bachelor's Degree in Computer ScienceFoundational CS degree demonstrating strong algorithmic thinking and systems-level understanding required for platform engineering

Master's Degree in Computer Science (Preferred)Advanced degree providing deeper expertise in distributed systems, data architecture, and scalable computing paradigms

Ph.D. in Computer Science (Preferred)Doctoral qualification indicating specialized research expertise in data systems, distributed computing, or related fields

Experience

7+ Years Production Systems ExperienceDemonstrated track record architecting, building, deploying, and supporting scalable production systems with proven ownership and operational excellence

5+ Years Cloud Platform ExperienceDeep expertise with AWS (primary) or GCP environments, including compute, storage, networking, and managed data services

5+ Years Big Data Query Engines ExperienceHands-on experience with modern data warehousing and querying platforms including Databricks, Snowflake, Redshift, and related technologies

5+ Years Distributed Systems DesignProven experience with large-scale distributed systems including scaling strategies, replication mechanisms, consistency models, and high-availability patterns

5+ Years Infrastructure as Code ExperienceProficiency with IaC tools like Terraform and Ansible for automated infrastructure provisioning, configuration management, and GitOps practices

Streaming Architecture & Event-Driven PipelinesDeep hands-on experience designing and implementing streaming systems with Apache Kafka, AWS Kinesis, Apache Flink, or similar technologies

Leadership & Mentoring ExperienceTrack record of leading through technical contribution, mentoring junior engineers, and fostering growth within engineering teams

Skills

Required skills

Streaming Architecture & Apache KafkaExpert-level design and implementation of event-driven data pipelines using Apache Kafka with Protobuf serialization for low-latency, high-throughput data flows

Data Warehouse & Query EnginesDeep operational expertise with Databricks and Snowflake, including performance optimization, cost management, and integration patterns between platforms

Distributed Systems DesignMastery of scaling principles, replication strategies, consistency models (eventual, strong), and high-availability architecture for production systems

Python ProgrammingProduction-grade Python proficiency for data engineering pipelines, infrastructure automation, and building scalable backend services

AWS Cloud PlatformsAdvanced AWS expertise including EC2, ECS, EKS, S3, VPC, IAM, KMS, and managed data services for building cloud-native data infrastructure

Infrastructure as Code (Terraform/Ansible)Expert-level IaC implementation using Terraform and Ansible for reproducible infrastructure deployment, version control, and automated provisioning

Schema Governance & Data QualityAbility to design and implement schema registries, data validation frameworks, quality monitoring, and comprehensive data lifecycle management

Cross-Functional CommunicationStrong communication skills enabling effective collaboration with engineering teams, data analysts, product managers, and business stakeholders on complex technical initiatives

Nice to have

Apache Flink & Stream ProcessingExperience with distributed stream processing frameworks for real-time data transformations, event aggregations, and complex windowing operations

Apache Iceberg & Table FormatsExpertise with Apache Iceberg for building unified storage layers with ACID transactions, time-travel capabilities, and schema evolution support

Dagster OrchestrationExperience with Dagster for data pipeline orchestration, dependency management, asset tracking, and observability-first workflow design

dbt Data TransformationProficiency with dbt for building modular, testable analytics data models and implementing data transformation best practices

Go & Scala/JavaAdditional proficiency in Go for systems programming or Scala/Java for compatibility with big data ecosystems and performance-critical components

Secure Systems & IAMDemonstrated expertise implementing least privilege access controls, encryption strategies, and compliance frameworks for sensitive data systems

Prometheus & Grafana ObservabilityExperience building comprehensive monitoring stacks using Prometheus for metrics collection and Grafana for real-time visualization and alerting

GCP Data PlatformSecondary cloud platform experience with Google Cloud Platform, including BigQuery, Dataflow, and managed data services

AI & ML Systems UnderstandingFamiliarity with AI/ML workload requirements, feature stores, ML pipeline infrastructure, and supporting data systems for production AI applications