Lead Analytics Engineer

Forward Financing

Lead Analytics Engineer guiding complex analytics engineering initiatives for a financial technology company. Driving the design of AI-ready data platforms and partnering with technical stakeholders.

Posted 7/1/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $160,000 - $185,000 per yearWebsite

Tech Stack

Tools & technologies

CloudSQL

About the role

Key responsibilities & impact

Own the technical architecture and roadmap for our most complex Analytics Engineering initiatives - including semantic layer design, source-of-truth consolidation, and the data foundation for AI and agent-based use cases
Architect Forward's semantic layer and metrics standards so key business KPIs are defined once, governed clearly, and consumed consistently across dashboards, models, AI agents, and downstream products
Lead the technical design of the AI-ready data platform - making the modeling, metadata, and governance decisions that make Snowflake Intelligence and other AI/agent capabilities trustworthy, performant, and production-ready
Drive technical excellence across our dbt project: model architecture, materialization and incremental strategies, performance tuning, macros, testing patterns, and CI/CD practices that scale as data volume and team size grow
Set and uphold a high bar for craftsmanship across the team - defining standards for SQL style, modeling patterns, documentation, and data quality, and modeling those standards in your own work
Mentor Senior and Analytics Engineers through hands-on code review, pairing, and design feedback - accelerating their growth into stronger technical contributors
Partner with the Manager of Analytics Engineering on technical strategy, hiring, and roadmap planning - acting as a deputy for technical decisions and unblocking the team on the hardest problems
Lead deep technical partnerships with Data Science, Data Engineering, and Core Technology - owning schema migrations, feature deployments, and streaming pipeline contributions where Analytics Engineering is on the critical path
Evaluate and operationalize high-value third-party data sources and emerging tooling (e.g., Snowflake Cortex, semantic layer frameworks, observability tools) and make recommendations that elevate the platform
Champion data governance and quality at the platform level - including dbt tests, lineage, cataloging, observability, and compliance with security and regulatory standards - so both stakeholders and AI systems can trust the numbers

Requirements

What you’ll need

6+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence
4+ years of hands-on production experience with dbt, including advanced patterns such as incremental strategies, macros, custom tests, and CI/CD design
3+ years of deep experience with a cloud-based data warehouse (Snowflake strongly preferred), including performance tuning and cost optimization
Expert-level proficiency in SQL and dimensional data modeling, with a portfolio of durable, well-tested models that have served as foundational layers for an organization
Demonstrated experience designing and operating a semantic layer or metrics layer that serves as an organizational source of truth
Proven ability to mentor senior engineers, lead architectural decisions, and influence direction across cross-functional teams
Excellent written and verbal communication skills - able to drive technical alignment with both engineers and non-technical stakeholders.

Benefits

Comp & perks

12% Annual Target Bonus
Fair and transparent compensation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Dimensional Data ModelingIncremental StrategiesMacrosCI/CD DesignPerformance TuningData Quality StandardsSemantic Layer DesignMetrics Layer DesignObservability ToolsData Cataloging

Soft Skills

MentoringTechnical CommunicationCross-Functional Collaboration