Forward Deployed Data Engineer - Houston

The Opportunity

As a Forward Deployed Data Engineer (FDE) on our US Launch Team, you will act as the principal technical anchor embedded directly within high-stakes enterprise client accounts (focusing heavily on Financial Services and Healthcare). You won't just be writing specs or advising from afar-you will be on the front lines in client environments, bridging the gap between C-suite data strategy and hands-on production code.

Working at the tip of the spear alongside our elite partners at Databricks and Anthropic, you will lead architecture design, modernize brittle legacy ecosystems into cloud-native Lakehouses, build agentic AI data harnesses, and guide integrated "SWAT" pods to ship working software in weeks rather than months.

Key Responsibilities

• Embedded Technical Leadership: Serve as the primary technical authority on client engagements. Partner directly with client VP/CTO stakeholders to scope architectures, map data domains, and turn complex requirements into execution-ready engineering plans.

• Hands-On Lakehouse Modernization: Roll up your sleeves to write and optimize production PySpark, Databricks SQL, and Delta Live Tables (DLT) -actively refactoring complex legacy logic (Informatica, PL/SQL, legacy stored procedures) into Medallion Architectures.

• Agentic AI & Data Infrastructure: Architect deterministic, secure data "harnesses" that integrate LLM workflows (Anthropic/Claude) into traditional enterprise data pipelines safely and cost-effectively.

• DataOps & IaC Ownership: Write modular Terraform scripts to provision cloud environments (AWS/GCP), manage governance and lineage via Unity Catalog, and enforce CI/CD rigor across projects.

• Pod & Delivery Guidance: Partner with our LATAM-based nearshore engineering squads (600+ experts) as the US technical lead-conducting code reviews, debugging performance bottlenecks, and maintaining high engineering standards.

• Technical Unblocking & Escalation: Act as the ultimate technical safety net. If a pipeline breaks or a deployment stalls at 2:00 AM, you have the hands-on depth to jump into the code, fix the issue, and keep client delivery on track.

Qualifications & Requirements

Technical Mastery & Execution

• Extensive Hands-On Data Engineering: Deep proficiency in Python and advanced SQL with a proven track record of shipping production data software.

• Deep Databricks Platform Expertise: Hands-on experience building, scaling, and tuning Databricks Lakehouse environments (Delta Lake, Unity Catalog, PySpark, DLT, Workflows).

• Modern Stack & IaC Discipline: Expert-level experience with dbt (Core or Enterprise) for data modeling, Terraform for Infrastructure as Code, and Git/Airflow for orchestration and CI/CD.

• Legacy Migration Experience: Demonstrated background migrating enterprise client workloads from legacy platforms (Teradata, Netezza, Informatica, Oracle) to modern cloud infrastructure.

Client Presence & Startup Grit

• The "Player-Coach" Mindset: Equal comfort pitching target architectures to a client CTO and debugging a failing PySpark job or dbt macro alongside junior engineers.

• Executive Communication: Ability to translate messy business requirements into clean architectural patterns and speak authoritatively across both technical and business functions.

• Scrappy Nation-Builder: High autonomy and resilience-thriving in a fast-paced, Series A growth environment without relying on rigid corporate playbooks or large support structures.

Nice-to-Haves

• Prior experience in forward-deployed, technical consulting, or ProServe roles at top-tier agencies or hyper-growth vendors.

• Pragmatic experience building or deploying LLM/GenAI orchestration frameworks (LangChain, LlamaIndex, Anthropic API) into production pipelines.

• Official certifications in Databricks, AWS, GCP, or dbt.

The anticipated base salary range for this role is $180,000 - $230,000. In addition to base pay, this position may be eligible for an annual discretionary bonus. An individual's final salary offer will be determined based on a variety of factors, including geographic location, experience, specialized skills, and qualifications. This compensation range is subject to updates or modifications at the company’s discretion