Technical Analytics Manager

You, the Technical Analytics Manager of our dreams, are the person clients and internal teams turn to when the data infrastructure itself needs to be right; not just the dashboard sitting on top of it. You think in data layers, not just metrics. You're as comfortable in a BigQuery console or a server-side GTM container as you are explaining to a client why their conversion counts don't reconcile across platforms. You own the technical backbone of measurement: how data is collected, transformed, governed, and ultimately trusted. This is a hands-on implementation and architecture role. You'll audit and build tracking infrastructure, own data pipelines from raw event to client-ready output, and make sure what gets reported is defensible, accurate, and built to last, not duct-taped together for one deliverable.

Role Highlights

Implementation & Architecture

Strategize and architect large-scale digital analytics implementations for a portfolio of clients, primarily on platforms like Google Analytics 4 and Adobe Analytics

Design, deploy, and maintain server-side tagging infrastructure (server-side GTM, first-party data collection, event routing) to improve data quality and resilience against browser/platform restrictions

Audit new and existing implementations to identify gaps, diagnose technical issues in code or configuration, and recommend the most feasible, durable solution

Confidently implement analytics and marketing tags through Tag Management Systems and CDPs (Google Tag Manager, Segment, or similar), and meet with developers, IT, and clients to design solutions that fit their technical environment

Data & Reporting

Build and maintain data transformation workflows that move raw platform exports into clean, modeled, analysis-ready tables in BigQuery

Build closed-loop measurement systems that connect marketing activity to downstream business outcomes (leads, pipeline, revenue) rather than stopping at platform-native conversions

Develop and maintain reporting and dashboarding in Looker Studio, (familiarity with PowerBI or Tableau familiarity a plus), translating complex data models into clear, decision-ready views for clients and internal stakeholders

Build measurement frameworks that move clients beyond sessions and conversions toward metrics that reflect real business outcomes and nonlinear customer journeys

Consent & Data Governance

Understand and implement consent management platforms and frameworks (e.g., Google/Microsoft Consent Mode v2, OneTrust) to keep tracking compliant with CCPA, GDPR, and other applicable privacy regulations

Evaluate and audit consent configurations for gaps, misconfigurations, or unintended data flows, and advise clients on remediation

Write clear technical documentation for team members, clients, and developers covering implementation logic, data flow, and governance decisions

AI-Native Execution

Use Claude and other AI tools daily to accelerate implementation QA, documentation, data transformation logic, and analysis

Build automations, workflows, prompts, and AI-assisted processes that improve how technical analytics work gets done

Treat pipelines, dashboards, and measurement frameworks as products that evolve over time, not one-time deliverables

Ask the question "How can AI help me build this?", rather than "How do I do this manually?"

Support experimentation and incrementality work where relevant (test design, holdout methodology, lift analysis) as a contributor to the broader measurement picture, not as a primary specialty

Challenge, coach, mentor, and provide feedback to peers and associates, helping elevate technical analytics capability across the team

Essential Skills

You have advanced analytics implementation expertise involving behavioral tracking, ecommerce measurement, and server-side data collection

You are comfortable working in BigQuery and can read, adapt, and maintain SQL for data transformation logic (dbt experience a plus, not required)

You have hands-on experience building and maintaining dashboards and reports in Looker Studio

You understand consent management architecture and privacy regulations affecting tracking (Consent Mode, CCPA, GDPR), and can audit existing configurations for gaps or compliance risk

You are confident deploying and troubleshooting Tag Management Systems and CDPs (server-side GTM, Segment, or similar), including custom integrations when off-the-shelf connectors don't exist

You have working familiarity with JavaScript (enough to read and adapt a data layer or GTM custom template), with Node.js or Python experience a plus for building custom connectors when off-the-shelf tools fall short

You can design and reason about closed-loop measurement, connecting marketing touchpoints to real business outcomes across systems (CRM, CDP, offline conversion imports)

You work effectively in AI tools, particularly Claude, to accelerate implementation, QA, and documentation as a daily working partner

You are naturally inclined to automate, improve, and simplify wherever possible, and you build workflows and repeatable systems that amplify impact

You take ownership of ambiguous technical problems, break them into actionable next steps, and bring solutions rather than just questions

You have strong organizational and project management capabilities and can manage your own workload and deadlines in a tool like Wrike, managing up when you hit blockers or competing priorities

You communicate effectively with technical and non-technical stakeholders, including translating data findings into executive-ready narratives

You have a strong sense of self, which means you can say no, deliver feedback, and confidently present the value you are driving for clients, even when things get challenging

You have a passion for mentoring teammates and elevating technical analytics capabilities across the team

Experience with Python, R, Node.js, or dbt for data transformation and custom integration work

Experience with additional data warehouses or ETL tools (Snowflake, Fivetran, etc.)

Exposure to experimentation frameworks, incrementality testing, or causal inference

Experience building automations, AI workflows, or internal tools

Experience in a consulting or agency environment

30/60/90 Day Goals

First 30 Days — Learn

Develop a strong understanding of Seer's analytics methodologies, client portfolio, and technical stack

Complete onboarding, shadow existing implementation work, and start building relationships across analytics, strategy, and client teams

Begin contributing to implementation audits, QA processes, and data pipeline reviews

Identify one quick win you can improve right away, such as a broken data flow, a manual process, or a dashboard

60 Days — Build

Independently manage technical analytics workstreams across multiple client engagements

Own a client-facing technical deliverable end to end, from data pull/transformation to presentation

Contribute to server-side tagging or consent configuration work on at least one client account

Begin contributing AI-assisted workflows or automations that improve how the team works

90 Days — Lead

Lead technical architecture conversations with clients (implementation, data flow, consent, closed-loop measurement)

Independently own a data pipeline or transformation layer supporting client reporting

Have at least one scalable system, dashboard, or tool in production that creates lasting value

Be a visible contributor to Seer's analytics practice, sharing ideas, improving processes, and raising the technical bar for the team

This might not be the right fit for you if...Compensation & Benefits