As a Data Engineer on our BI team, you’ll be a key player in Motive’s growth, delivering the data infrastructure for the AI era. You’ll act as the essential link between complex data and key business domains, delivering the high-quality datasets and semantic models that drive global strategy. This is an exciting opportunity to implement cutting-edge tooling, leverage AI to enhance your workflow, and master a modern data stack in a fast-evolving environment.

This is the perfect role for a "jack of all trades" data practitioner. You’ll design data models, build robust pipelines, manage DevOps and automated systems, and implement AI-driven data tooling. You’ll even get your hands dirty building dashboards and performing deep-dive analysis. If you love working full-stack and owning the entire data lifecycle, you’ll love this role.

What You'll Do:

• Collaborate & Strategize: Partner closely with business stakeholders to understand their challenges and design end-to-end architecture that solves complex business problems.
• Build & Maintain Data Models: Design, develop, and own robust, efficient, and scalable data models in Snowflake and Iceberg using dbt and advanced SQL.
• Orchestrate & Automate: Build and manage reliable data pipelines and CI/CD workflows using tools like Airflow, Python, and Terraform to ensure data is fresh, trustworthy, and infrastructure is version-controlled.
• Champion Data Quality: Implement rigorous testing, documentation, and data governance practices to maintain a single source of truth.
• Enable Analytics & Workflows: Act as the Product Owner and Tech Lead for your data domains, taking responsibility for the end-to-end data product delivery– from raw ingestion to data models enabling analytics and data apps in tools like Tableau and Retool.
• Innovate with AI: Help us build our next-generation data infrastructure by integrating AI capabilities (like Snowflake Cortex AI) to democratize analytics and empower the business.
• Architect Observability: Implement monitoring and alerting frameworks (e.g., dbt packages or  Monte Carlo monitors) to proactively catch "silent" data failures before stakeholders do.

What We're Looking For:

• 6+ years of experience in Analytics Engineering, Data Engineering, or a similar role.
• Deep expertise in SQL and developing complex data models for analytical purposes (e.g., dimensional modeling).
• Hands-on experience with:
  • Data Warehousing: High proficiency in Snowflake (preferred) and experience with Open Table Formats like Iceberg.
  • Data Transformation: dbt
  • Orchestration & ETL: Airflow, Fivetran, Airbyte
  • Cloud Platform: AWS
  • Programming/Ingestion: Python
  • Infrastructure as Code: Terraform
  • AI-Augmented Development: Proficiency using AI coding assistants (Cursor, Copilot, or Claude) to accelerate development and automate routine tasks.
• A strong analytical mindset with a proven ability to solve ambiguous business problems with data.
• Excellent communication skills and experience working cross-functionally.
• Self-starter with the ability to self-project manage work
• A user focus with the ability to understand how a data consumer will use the data products you build

Bonus Points (Nice-to-Haves)

• Experience building semantic models for natural language querying
• Direct experience with advanced Snowflake features (e.g., Snowpark, Cortex AI).
• Experience building visualizations and dashboards in tools like Tableau,  Retool, or Thoughtspot.

We’re seeking a Staff DevOps Engineer to join our Cloud Platform Team — the engineer who sets the technical direction for how Built’s infrastructure is designed, operated, and evolved. This is the most senior individual contributor role on the platform team, and it goes well beyond day-to-day operations. You’ll architect the systems that every engineering team at Built depends on, define the standards that others work within, and drive the platform roadmap with full autonomy. By raising the reliability and velocity of our infrastructure, you directly enable Built’s mission of radically disrupting construction finance.

Our Guiding Principles

• Be Bold. We pursue the biggest problems in our industry, challenge assumptions others take for granted, and take calculated risks to get there. We don’t hide behind consensus or committees. Playing it safe is just failing slowly.
• Help Customers Win. We learn our customers’ businesses deeply — how they think, how they deploy capital, what keeps them up at night. We treat their capital like our own. We ship leverage, not features. And we measure ourselves by customer results, not our intentions.
• Move with Urgency & Purpose. We bias toward delivery over perfection, remove friction from our own paths, and communicate in real time. Momentum compounds — and we build it every day.
• Own the Outcome. We own outcomes, not just tasks. We hold a high Say:Do ratio and take responsibility from idea through impact. When something breaks, we fix it — we don’t wait to be asked.
• Never Satisfied. We raise the bar continuously. We stay curious, hold exacting standards, debate hard, and hold our opinions loosely when the evidence shifts. Excellence is a habit, not an event.

What You’ll Do

• Architect and own Built’s core cloud infrastructure on AWS — defining the patterns, standards, and systems that all engineering teams build on, from EKS/ECS cluster design to VPC topology to IAM governance.
• Lead platform modernization — driving the migration and simplification of our software delivery lifecycle, rationalizing tooling, and building the infrastructure foundation for Built’s AI-related product initiatives.
• Own SLOs and SLIs for the platform — define them, instrument them in your observability stack, and lead the team in meeting reliability targets consistently across all environments.
• Define DevOps engineering standards across the team — IaC patterns, CI/CD architecture, container orchestration standards, and observability frameworks.
• Drive the platform roadmap in partnership with engineering leadership — balancing foundational investment with immediate delivery needs and communicating trade-offs clearly to technical and non-technical stakeholders.
• Lead incident response and postmortems — serve as the technical escalation point for complex infrastructure failures, drive systemic improvements, and reduce incident volume over time.
• Evaluate and adopt new technologies across the platform stack — making sound build-versus-buy decisions with a clear view of long-term trade-offs and ROI.
• Mentor a team of 5 platform engineers through design reviews, pairing, architecture guidance, and knowledge-sharing sessions across the broader engineering organization.
• Partner with Information Security to lead vulnerability assessment and security architecture — ensuring compliance, proactive risk management, and adherence to regulatory requirements.

Skills & Experience

Must-Have

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 8+ years of hands-on experience in DevOps, platform engineering, or cloud infrastructure in a production environment.
• Expert-level AWS knowledge — deep fluency with EKS, ECS, EC2, RDS, S3, IAM, VPC, and cost management tooling.
• Deep Kubernetes expertise — cluster architecture, networking, RBAC, autoscaling, and debugging production workloads at scale.
• Strong infrastructure-as-code proficiency with Terraform — writing extensible, maintainable modules and enforcing IaC standards across the team.
• Proven experience designing and operating CI/CD pipelines with GitHub Actions, CircleCI, or similar tooling.
• Hands-on observability experience with Datadog, Grafana, or similar platforms — metrics, logs, traces, monitors, SLO tracking, and alerting.
• Familiarity with incident management tooling (Incident.io, PagerDuty, or similar) and a track record of leading postmortems and driving systemic reliability improvements.
• Fluency in at least one scripting or automation language — Python, Go, or Bash.
• Strong communication skills — able to present infrastructure risks and architectural trade-offs to both engineers and non-technical stakeholders.

Nice-to-Have

• Experience with other IaC tools (Pulumi, CloudFormation, CDK) is a plus.
• Experience with service catalog and developer experience tooling (OpsLevel, Backstage, or similar).
• Background in fintech, lending, or regulated industries where uptime, auditability, and data security are critical.
• FinOps experience — cloud cost governance, right-sizing, and spend transparency across engineering teams.
• Contribution to open-source infrastructure projects or published engineering RFCs.

What the First Year Looks Like

Days 1–30: Learn the Landscape

• Ramp up on Built’s AWS infrastructure (EKS, ECS, VPC, IAM), CI/CD pipelines, and observability stack.
• Shadow on-call rotations (roughly one week every six weeks) to understand current incident patterns and pain points firsthand.
• Build relationships with product engineering teams to understand their infrastructure dependencies and friction points.

Days 30–60: Start Shaping the Platform

• Identify the highest-leverage opportunities for platform modernization and SDLC simplification.
• Begin contributing to architecture decisions and TRDs for current initiatives.
• Propose improvements to IaC standards, deployment pipelines, or observability coverage where gaps exist.

Days 60–90: Own and Drive

• Lead a meaningful platform initiative from architecture through delivery — whether modernization, reliability, or developer experience.
• Establish yourself as the technical standard-setter the team turns to for complex infrastructure and AI-related platform questions.
• Contribute to the roadmap planning process with a clear point of view on what the platform needs next.

AI & Technology Expectations

At Built, AI is a first-class part of how we work — not a pilot program. For this role specifically, that means:

• Use AI coding assistants (your choice of platform) as a daily productivity multiplier for IaC authoring, pipeline configuration, and automation scripting.
• Apply AI to platform operations: runbook generation, incident summarization, root cause analysis drafts, and postmortem synthesis.
• Drive and contribute to Built’s broader initiative to automate the software delivery lifecycle — identifying where AI can reduce manual toil across build, test, deploy, and observe workflows.
• Evaluate emerging AI infrastructure tooling and bring well-reasoned recommendations to the team.
• Share effective AI use cases and patterns with the broader engineering organization.

Operational Details

• Team size: You’ll join a team of 5 platform engineers, with this role serving as the senior technical anchor.
• On-call: Rotations run approximately one week every six weeks. We work continuously to reduce incident volume and toil so that on-call is manageable and low-noise.
• Location: Remote (US). Flexible working hours.

Built’s salary range for this position is $175,000-$235,000 USD per year. The pay range is designed to accommodate upward mobility in the role, therefore it encompasses the full span of proficiency levels for this role and we believe that the midpoint of the range is competitive in the market. Salary is just one component of Built's total compensation package for employees. Your total rewards package at Built will include equity, top-notch medical, dental and vision coverage, an unlimited PTO policy, and other benefits.