Senior Data Engineer

At BuildOps, we’re building software purpose-built for commercial contractors. From service to projects, we help our customers run the workflows that keep buildings, businesses, and critical infrastructure operating.

The Analytics team owns the data platform behind that software. That includes the pipelines that pull product data into Snowflake, the dbt models customers and internal teams rely on, the embedded reporting inside our product, and the secure data shares our strategic customers query from their own environments.

The work is customer-facing and high-stakes: customers run their businesses on numbers that come through our platform. We have a wide mandate and are hiring a senior engineer who wants to own meaningful parts of it.

What You'll Do

Core platform & modeling work (about 70% of your time):

• Build and scale ingestion: Own CDC pipelines from our operational MySQL and Postgres sources into Snowflake using Airbyte and Streamkap, plus third-party sources across the business, including recovery when things go wrong
• Drive down latency: Help move us from batch toward near-real-time, using Snowflake dynamic tables, incremental dbt design, and orchestration redesign; customers increasingly expect data within minutes, and you'll help decide how far and how fast we can get there
• Model the business: Design and maintain layered dbt models (staging, intermediate, marts) across every product domain; getting correctness right, including history, grain, and reconciliation, matters as much as speed
• Grow customer data sharing: Evolve our multi-tenant Snowflake Secure Data Sharing and our open-format (Apache Iceberg) sharing for customers on other platforms, including tenant isolation, cross-region and cross-cloud fulfillment, and schema-change contracts
• Harden the platform: Build SLA, freshness, and completeness instrumentation; mature our deployment process so we stop pausing pipelines to ship; extend Terraform coverage of Snowflake, and keep warehouse cost and performance in check
• Raise the bar: Write design docs, review code, mentor engineers, and make architecture calls that hold up over time

On-call & partner support (about 30%):

• Take a full-sprint on-call rotation covering pipeline incidents, data share fulfillment, report breakages, and data accuracy escalations
• Unblock product squads, Finance, CS, RevOps, and Marketing on data delivery and internal analytics
• Handle Snowflake access, roles, and governance work alongside DevOps and IT

What We Look For

• 5+ years in data engineering, with production pipelines you've owned end to end
• Deep Snowflake experience: warehouse sizing and performance, RBAC, and ideally data sharing, dynamic tables, or Iceberg
• Strong dbt: incremental strategies, testing, layered modeling, and knowing when a full refresh will hurt you
• Hands-on CDC and ingestion experience with tools like Airbyte, Debezium, Streamkap, Fivetran, or Kafka, plus a working understanding of binlogs and replication
• Airflow, preferably at production scale (MWAA is a plus)
• Strong SQL and Python
• Solid AWS fundamentals
• Experience working in a multi-tenant SaaS data environment
• Calm, methodical incident response, and the judgment to fix problems at the right layer
• Clear written communication, both for design docs and for explaining a data issue to a non-technical stakeholder

Nice To Have

• Experience with event-sourced systems
• Embedded BI (Sigma or similar), including row-level security
• Terraform for Snowflake or other data infrastructure
• Data catalog and governance tooling such as Secoda, lineage, and data contracts
• Real-time analytics architecture, with an honest view of its cost tradeoffs
• Using AI coding tools such as Claude Code in your daily workflow

Our Stack

• Snowflake
• dbt
• Airflow (MWAA)
• Airbyte
• Streamkap
• Sigma
• Secoda
• AWS
• Terraform
• Apache Iceber
• GitHub

Compensation:

• $120,000 - $197,000 base salary range + annual bonus + stock op