Data Architect

Remote

Expel

Expel is a recognized, leading managed detection and response provider with a 20-minute MTTR on high/critical incidents.

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At Expel, we bridge the cybersecurity talent gap with our MDR platform that enables industry-leading rapid detection and response to security threats. As we continue to scale, we are looking for a Data Platform Architect to evolve our architecture including the semantic layer to drive innovation and support our growth across the business.

You’ll play a critical role in optimizing our legacy platform while integrating new patterns like medallion architecture to ensure scalability, performance, and data quality. 

We’re not looking for someone to work in isolation or on a blank slate. As a thriving business valued at over $1bn, we need a hands-on architect who will collaborate with software engineers, data scientists, and product teams to tackle real-world challenges. Whether it’s modernizing legacy systems or optimizing new data lakes, your technical intuition and pragmatic approach will guide teams through the intricacies of today’s data architectures.

Your ability to align technical vision with business needs will be key to ensuring that data continues to drive company success. Since this role involves leading architecture across multiple teams, working closely with principal and senior engineers, we place high value on leadership and interpersonal skills. Even if you only meet 70% of the technical requirements, we encourage you to apply—you likely have the intuition to ask the right questions and make informed decisions.

What Expel can do for you:

  • Give you the opportunity to craft the future of our data platform, while guiding its maturation at the center of a fast-growing cybersecurity company where data is a key strategic asset.
  • Collaborate with passionate engineers, data scientists, and product teams who care deeply about innovation, quality, and technical excellence.
  • Provide the freedom to build and implement data strategies that directly impact the business.
  • Enable you to engage in multi-functional initiatives, collaborating with R&D and business systems teams to solve complex data challenges.
  • Support your personal and professional growth through educational opportunities, mentorship, and leadership development.

What you can do for Expel:

  • Help guide Expel toward a mature data strategy improving data lineage, quality, and governance across the organization.
  • Architect, evolve, and optimize Expel’s data platform to meet the needs of a fast-scaling service.
  • Collaborate with teams to improve data pipelines, storage, access, and governance, ensuring high data quality and accessibility.
  • Further collaboration among Data Science, Product Engineering, and other teams to eliminate data silos and inefficiencies in a multi-functional manner.
  • Be a key player in the Architecture Guild, working to advance data storage, format, and governance strategies across the company.
  • Communicate the value of Expel's data architecture to internal and external collaborators, including customers and partners.

What you should bring with you:

  • Proven experience in leading the overhaul of existing data architectures, resulting in significant improvements to business performance across multiple dimensions. This includes mentoring teams and individuals to successfully implement your design enhancements.
  • A methodical, iterative approach that prioritizes building and measuring quality, scalability, and performance at every stage of a project.
  • Deep, hands-on expertise in cloud-based data platforms, with a strong track record across one or more major providers (e.g., Google Cloud, AWS, Azure). This includes a comprehensive understanding of architecture, services, and best practices for designing scalable, secure, and cost-effective data solutions tailored to complex business requirements.
  • Expertise in data formats, query engines, and table setup, with deep knowledge of SQL and NoSQL optimization, and the ability to choose the right database (Relational, Graph, Vector DB) for the job. This includes balancing tradeoffs, such as when to use a lakehouse vs. warehouse or both to deliver the most value.
  • Proficient in distributed data processing frameworks (e.g., Apache Spark, Flink) with hands-on expertise in programming languages such as Python, Golang, or Java, enabling efficient large-scale data processing in data lakes.
  • Thorough understanding of data governance, security, and regulatory compliance, with a proven ability to implement frameworks that ensure data integrity, secure access, and alignment with industry standards.

Additional notes:

The base salary for this role is $183,700 - $266,400 + bonus and equity.

At Expel, our employee benefits reflect our commitment to our crew. Unlimited PTO, equity for everyone, work location flexibility, up to 24 weeks of parental leave, and excellent health benefits are some of the ways we care for our Expletives.

We’re only hiring those authorized to work in the United States. We do not currently sponsor immigration visas.

We're an Equal Opportunity Employer: You'll receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.

We’ll ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please let us know if you need accommodation of any kind.

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Salary Range$183,700—$266,400 USD
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Category: Architecture Jobs

Tags: Architecture AWS Azure Data governance Data pipelines Data quality Data strategy Engineering Flink GCP Golang Google Cloud Java NoSQL Pipelines Python R R&D Security Spark SQL

Perks/benefits: Career development Equity / stock options Health care Parental leave Salary bonus Startup environment Unlimited paid time off

Regions: Remote/Anywhere North America
Country: United States

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