Lead Data Engineer - AI Analytics Infrastructure | Faire NEW

The Briefed; San Francisco (CA); Ibrido; USD 196.000 - 270.000; Tempo pieno

Vantaggi offerti da questo lavoro

Competitive equity

Hybrid schedule

Parental leave

Medical/dental/vision

Wellness stipend

Professional development

Home office stipend

Retirement plan

Descrizione del lavoro

Faire seeks a Lead Analytics Engineer to bridge analytics and data engineering, shaping product features for SMBs. You will design scalable data models and pipelines, while pioneering AI-enabled analytics operations to automate workflows and improve data quality and security.

You will collaborate with Data Scientists, Product Analysts, and Software Engineers to align data architecture with product roadmaps and strategic insights.

Competenze

• 4+ years of analytics and data engineering experience.
• Production-level Python development.
• Expert SQL and data modeling skills.
• Experience with data warehousing and ETL/ELT pipelines.
• Hands-on experience with Airflow, Docker, dbt.
• Strong technical leadership and communication.
• BA/BS in CS/Math/Physics or related field.

Mansioni

• Design, architect, and scale high-performance data models and pipelines.
• Lead cross-team data engineering initiatives from design through production deployment.
• Embed AI capabilities into analytics workflows.
• Ensure data quality, observability, and security across data systems.
• Partner with Data Scientists, Product Analysts, and Engineers.

Conoscenze

Python

SQL

Data Modeling

Airflow

dbt

Docker

Big Data

Leadership

Communication

Python Development

Formazione

BA/BS in CS/Math/Physics or related field

Strumenti

Airflow

Docker

dbt

Descrizione del lavoro

As a Lead Analytics Engineer, you will serve as a technical leader bridging analytics and data engineering to shape Faire's product features for small and medium businesses (SMBs). Working closely with Data Scientists, Product Analysts, and Software Engineers, you will design, architect, and scale high-performance data models and pipelines that power product roadmaps and strategic insights. In this role, you will pioneer the integration of AI tools directly into daily analytics engineering operations - automating routine pipeline creation, streamlining data consumption workflows, enhancing observability, and raising the operational bar for data quality and security across Faire's data ecosystem.

Key Responsibilities

AI Data Pipelines & Scalable Architecture

• AI-Driven Engineering Workflows: Redefine how analytical engineering operates by embedding AI capabilities into daily workflows - streamlining data pipeline development, automating ETL operations, and optimizing data consumption.
• Domain Architecture & Modeling: Lead the technical execution and architectural strategy for building scalable, high-throughput domain data models and data pipelines across company-wide product initiatives.
• Data Quality & Observability: Build data pipelines with rigorous standards for data validation, automated testing, quality guardrails, data lineage, and continuous observability.
• Operational & Security Excellence: Optimize project management processes for operational reliability while enforcing strict data security standards and governance policies across data systems.

Cross-Functional Technical Leadership

• Project Execution: Lead cross-team and multi-phase data engineering initiatives from technical design through production deployment, fostering collaboration across Product, Data Science, Strategy, and Engineering.
• Stakeholder Enablement: Partner with key analytical partners to translate complex SMB product requirements into intuitive, self-service data capabilities.
• Technology Adoption: Evaluate and champion emerging big data technologies, analytics platforms, and AI tools to continuously modernize Faire's data stack.

Requirements

Technical Depth & Analytics Engineering Mastery

• Experience Track: 4+ years of professional experience in analytics and data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics/data science.
• Python Development: Production-level software engineering experience in Python.
• SQL & Data Modeling: Expert-level SQL skills with demonstrable competencies in designing well-architected, scalable data models and optimizing query performance across large datasets.
• Data Warehousing & ETL: Deep understanding of data warehousing concepts, enterprise ETL/ELT pipelines, big data technologies, and modern analytics platforms.
• Analytics Workflow Tooling: Hands-on experience with orchestration and transformation tools such as Airflow, Docker, dbt, or equivalent analytics workflow frameworks.
• Technical Communication & Leadership: Proven track record of steering complex, multi-stakeholder technical projects, communicating technical architecture clearly to non-engineering leadership.
• Education: BA/BS degree in Computer Science, Mathematics, Physics, or a related quantitative technical field.

Preferred Qualifications

• Experience building data models for two-sided marketplaces, e-commerce, or B2B SaaS platforms.
• Familiarity with Snowflake, Databricks, PySpark, or real-time streaming architectures.
• Experience utilizing LLM code assistants and automated data testing frameworks (e.g., Great Expectations, Anomalo, dbt tests).

Total Rewards & Benefits

• Compensation & Equity: California base salary range ($196,000 - $269,500 USD) + competitive equity grants + comprehensive benefits package.
• Time Off & Workplace Flexibility: Flexible Paid Time Off (PTO), company-wide recharge days, and 4 weeks of remote work flexibility annually for hybrid employees.
• Family & Parental Support: Paid parental leave (up to 16 weeks) alongside comprehensive family-building and fertility benefits through Carrot (including a lifetime reimbursement allowance).
• Health & Mental Wellbeing: Comprehensive medical, dental, and vision insurance coverage, plus mental health support and dedicated coaching through Modern Health.
• Stipends & Retirement: Professional development stipends, wellness allowances, work-from-home setup stipends, and an employer-sponsored retirement plan.