Snowflake/DBT

Advanced Analytics & Data Platform Lead

Overview
We are seeking a highly technical and product-minded analytics player-coach to drive the development, governance, and evolution of our Data and Analytics platforms. This role spans Snowflake administration, KPI data governance, pipeline development, and advanced analytics enablement - ensuring that data is transformed into reliable, reusable, and value-generating products.

The focus is on building trustworthy data foundations (customer 360, KPI canon, and governed data products) that can power reporting, marketing activation, and ecommerce personalization. This leader will also manage a small but impactful team of 1-2 analysts.

Key Responsibilities

Data Products, Identity & KPI Governance

Define, document, and govern the organizational KPI canon across business units.

Build and maintain a customer 360 data foundation, including unified account, practice, and person-level hierarchies.

Leverage statistical and ML techniques where appropriate to support identity resolution, deduplication, and hierarchy building.

Partner with Marketing and Product to ensure segmentation, personalization, and targeting needs are supported by governed, reusable data products.

Translate business KPI definitions into technically sound implementations that scale across dashboards and activation workflows.

Platform & Administration

Own the Snowflake environment: configuration, optimization, security, and governance.

Manage integrations with Product, Marketing, Finance, Vendor Services, and Customer Service teams to ensure data products are activation-ready.

Design schemas and pipelines that support both batch analytics and near-real-time event data for behavioral segmentation.

Execute reverse ETL workflows and API-based integrations to connect Snowflake outputs into downstream applications.

Leverage AI-assisted development tools (e.g., for SQL, dbt, pipeline scripting, documentation) to increase efficiency and consistency.

Implement orchestration workflows (e.g., Airflow, Dagster, Prefect) to ensure reliable, automated data delivery.

Analytics & Dashboards

Partner with Analysts to deliver governed, business-ready dashboards.

Ensure dashboards are prioritized, consistent with the KPI canon, and aligned to the customer 360 data foundation.

Oversee dashboard governance to ensure reporting reflects accurate, trusted, and consistent metrics.

Governance, Segmentation & Operations

Execute against the roadmap by operationalizing customer identity resolution, segmentation, and audience activation capabilities.

As maturity advances, use ML techniques to support behavioral segmentation and audience scoring.

Manage the execution backlog, ensuring delivery of high-value analytics and data products.

Enforce data quality, lineage, and observability standards across all data products.

Evaluate and implement AI-powered monitoring, anomaly detection, and data quality checks to improve reliability.

Incorporate third-party enrichment sources where appropriate to expand customer intelligence.

Document audience definitions, data lineage, and measurement frameworks for transparency and reproducibility.

Collaboration & Leadership

Act as the technical bridge between Marketing, Data & Analytics, Services, and Engineering to deliver on customer data use cases.

Translate stakeholder-defined needs into governed, production-ready data products.

Manage and mentor a two-person team (BI Analyst and Analytics Engineer), providing coaching, career development, and resource allocation.

Coach the team on effective and responsible use of AI assistants for coding, documentation, and analysis while ensuring outputs meet governance and compliance standards.

Foster a collaborative culture that values transparency, governance, and technical excellence.

Predictive Modeling & ML Ops

As organizational maturity advances, build and optimize predictive models in partnership with business stakeholders, ensuring they are monitored, retrained, and aligned with business KPIs.

Support feature engineering and audience modeling for segmentation, personalization, and operational efficiencies.

Productionize models and integrate outputs into governed data products and activation workflows.

Skills & Qualifications

6+ years in analytics engineering, data product management, or advanced analytics leadership.

Deep expertise in Snowflake administration (warehouses, RBAC, optimization, cost management).

Strong SQL and experience with dbt (or similar modern data modeling frameworks).

Proven ability to design customer 360 data models and implement identity resolution workflows.

Hands-on experience with reverse ETL tools, API integrations, and orchestration frameworks.

Experience defining and governing KPIs from the data side, ensuring consistency across BI and marketing use cases.

Familiarity with AI-assisted development tools (e.g., Copilot, ChatGPT, SQL generation assistants) and their application in data engineering, analytics, and documentation.

Strong communication skills to partner with both technical and non-technical stakeholders.

People management experience (leading small analytics/engineering teams).

Bonus: prior exposure to marketing data activation, customer data platforms, real-time event streaming, or predictive analytics.