Head of Data Engineering

Go Cadre • San Diego, CA

3h

About The Position

We are looking for a Head of Data Engineering to build and lead Cadre AI’s Data Engineering practice from the ground up. This is a senior, hands-on leadership role responsible for architecting and scaling multi-tenant Snowflake data warehouse solutions—both for internal operations and as a core service offering for our clients.
You will serve as the technical authority on all things data infrastructure, working directly with clients to design cloud-native data platforms, build modern ELT/ETL pipelines, and establish data governance frameworks. As the practice grows, you will recruit and mentor a team of data engineers, evolving this function into a standalone revenue-generating practice within Cadre AI.
This role is ideal for someone who thrives at the intersection of deep technical execution and client-facing consulting—someone who can whiteboard a Snowflake architecture in the morning, pair with engineers on dbt models in the afternoon, and present a data strategy roadmap to a client’s leadership team by end of day.

Requirements

• 8+ years of professional experience in data engineering, data architecture, or a related technical role.
• 3+ years of hands-on experience with Snowflake as a primary data platform, including advanced features (Snowpark, Snowpipe, Tasks, Streams, Dynamic Tables).
• 3+ years in a client-facing consulting, professional services, or agency environment.
• Deep expertise in SQL, Python, and modern data transformation tools (dbt strongly preferred).
• Strong experience with cloud platforms (AWS preferred; Azure and GCP also valued) including infrastructure-as-code tools like Terraform.
• Proven experience designing multi-tenant data architectures with robust access control, data isolation, and cost allocation.
• Experience with data pipeline orchestration tools such as Airflow, Dagster, Prefect, or Databricks Workflows.
• Demonstrated ability to lead technical teams and grow a practice or function from early stage.
• Exceptional communication skills—ability to present to C-suite executives and collaborate with junior engineers equally effectively.
• Strong understanding of data governance, data quality frameworks, and regulatory compliance (SOC 2, GDPR, CCPA).
• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience).

Nice To Haves

• Snowflake SnowPro Advanced certifications (Architect, Data Engineer).
• Experience with Snowflake Cortex AI, Streamlit in Snowflake, and AI/ML data preparation workflows.
• Familiarity with complementary platforms: Databricks, Microsoft Fabric, Redshift, BigQuery.
• Experience building data products or analytics-as-a-service offerings for external customers.
• Background in industries Cadre AI serves: mortgage/financial services, IoT, SaaS, or professional services.
• Experience with real-time data pipelines (Kafka, Kinesis) and streaming architectures.
• Track record of contributing to the data community through speaking engagements, open-source contributions, or published content.
• Experience managing P&L responsibility or practice-level financial metrics in a consulting environment.

Responsibilities

• Design, build, and optimize multi-tenant Snowflake data warehouse architectures for Cadre AI and its clients, ensuring scalability, security, and cost efficiency.
• Develop and maintain modern ELT/ETL pipelines using tools such as dbt, Airflow, Fivetran, and custom Python-based ingestion frameworks.
• Implement data modeling best practices (star schema, snowflake schema, Data Vault) tailored to each client’s analytical and operational needs.
• Establish data governance, quality, and lineage frameworks across multi-client environments.
• Drive cloud infrastructure decisions on AWS, Azure, or GCP with a focus on Snowflake-native capabilities including Snowpark, Cortex, Streamlit, and Snowpipe.
• Build repeatable reference architectures, accelerators, and templates that can be deployed across client engagements to improve delivery speed and consistency.
• Serve as the senior technical advisor and trusted consultant to clients on data strategy, architecture, and implementation.
• Lead discovery sessions, technical assessments, and data maturity evaluations for prospective and current clients.
• Translate complex business requirements into scalable data solutions and present technical roadmaps to executive stakeholders.
• Provide executive oversight on multi-client data engineering programs, ensuring projects are delivered on time, within scope, and at high quality.
• Support pre-sales efforts including scoping, estimation, proposal development, and technical solution design.
• Build and scale the Data Engineering practice from the ground up—define the service offering, pricing model, delivery methodology, and team structure.
• Recruit, hire, and mentor data engineers as the practice grows, establishing a high-performance team culture grounded in technical excellence and client service.
• Develop and maintain internal knowledge bases, playbooks, and training materials for data engineering best practices.
• Collaborate with Cadre AI’s pod leads, AI engineers, and solutions architects to integrate data engineering into broader AI transformation engagements.
• Track practice KPIs including utilization, revenue, client satisfaction, and delivery quality.
• Represent Cadre AI as a subject matter expert in the Snowflake and modern data stack ecosystem.
• Build and maintain relationships with Snowflake account executives, partner managers, and solution engineers.
• Contribute to Cadre AI’s brand through blog posts, conference talks, community engagement, and technical content.
• Stay current on emerging data technologies and evaluate their applicability for client solutions (e.g., Databricks, Microsoft Fabric, BigQuery, Iceberg/Delta Lake).

Benefits

• Ground-floor opportunity to build and own an entire practice within a rapidly scaling AI firm.
• Direct access to leadership—work alongside the co-founders and shape company strategy.
• Diverse, high-impact client engagements across industries with real AI transformation problems to solve.
• Pod-based team culture that values autonomy, ownership, and craft.
• Competitive compensation with performance-based upside as the practice scales.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level