Engineering Execution

• Own technical prioritization and delivery across a team of 8+ engineers; drive sprint-level execution and quarterly delivery commitments.
• Lead incident response and root-cause analysis for production issues; build systemic fixes, not one-off patches.
• Make and defend build-vs-buy decisions for Lakehouse components based on strategic fit and engineering cost.
• Establish and maintain engineering standards: testing practices, observability instrumentation, and release safety specific to data infrastructure.

People and Team Development

• Coach engineers at all levels — technical mentorship, growth plans, and direct performance feedback delivered consistently.
• Hire and develop senior ICs and tech leads; build team depth to reduce knowledge concentration risk.
• Model the builder culture: write code, ship internal tools, and set the bar for technical craft on your team.

AI-Forward Development

• Champion AI-assisted development practices across the team — your own workflow should demonstrate what good looks like.
• Identify opportunities to apply AI to data quality, schema inference, anomaly detection, and platform observability on the Lakehouse layer.
• Contribute to TetraScience's broader AI platform strategy from the Lakehouse data infrastructure layer up.

Requirements

WHAT YOU WILL BRING

Required

• 10+ years of engineering experience at top tier technology organizations, with at least 4 years focused on data engineering or distributed systems at production scale.
• Demonstrable expertise in Lakehouse technologies: Apache Spark, Delta Lake or Apache Iceberg, Databricks or an equivalent distributed compute platform.
• Experience leading Data Engineering teams (6+ engineers) with direct accountability for strategy, execution, operational excellence and people development.
• Strong command of distributed systems, cloud and modern data stack: columnar and open table formats, query execution engines, partitioning strategies, metadata catalogs and decoupled storage and compute platforms
• Track record of building, shipping and operating Tier 1 production data platforms and products.
• Cloud-native fluency: AWS, GCP, or Azure, containerization, and Infrastructure-as-Code (Terraform or equivalent).
• Clear written and verbal communication; can present architectural decisions to both technical and non-technical stakeholders.

Strong Advantage

• Experience in regulated industries (life sciences, healthcare, financial services) with data governance and auditability requirements.
• Familiarity with scientific data pipelines, analysis or instrument data pipelines.
• Real-time or near-real-time streaming experience (Kafka, Apache Flink, or equivalent).
• Exposure to AI/ML workflows over Lakehouse data: feature stores, ML pipelines, or vector search infrastructure.
• Prior career arc as a senior IC (Staff+ / Principal Engineer equivalent) before moving into engineering leadership.

WHY TETRASCIENCE

• Mission-driven: your infrastructure directly enables scientific drug development processes that save and extend lives.
• Builder culture: everyone ships — engineers, managers, and leadership. No passengers.
• Technically ambitious: we are rebuilding how science-grade data infrastructure works, not deploying off-the-shelf solutions.
• AI-first: we apply AI across every layer of the platform today, not as a future roadmap item.
• Competitive compensation, meaningful equity, and strong benefits.

Benefits

• ​Competitive compensation
• Stock options in a VC-backed Series C company
• 100% employer-paid benefits for all eligible employees and immediate family members
• 401(k)
• Unlimited paid time off (PTO)
• Flexible working arrangements
• Company-paid Life Insurance, LTD/STD

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