Senior Manager, Growth Marketing Technology Engineering

People Inc•New York, NY

1d•$100,000 - $124,000•Hybrid

About The Position

About the Role The Senior Manager of Growth Marketing Technology Engineering is a senior, hands-on role within the Audience Relationships Team, sitting at the intersection of platform operations, growth marketing, and data engineering. The Senior Manager will own the technical backbone of our growth and lifecycle marketing stack while acting as a strategic partner to Marketing, Data, and Product. This role is not a traditional marketing ops position and not a pure data engineer role. We are looking for a highly technical marketer or a technical platform engineer who has transitioned into growth marketing, with deep hands-on experience building, automating, and scaling activation systems. The mandate is to make growth faster, smarter, and more automated by deeply understanding our tools, data flows, and customer signals, then engineering them into reliable and repeatable systems. Hybrid 3x a week- (New York City) In-office Expectations: This position is hybrid in-office, with the ability to work remotely for up to 2 days per week.

Requirements

6–8 years of experience in marketing operations, martech, or data activation roles.
Advanced SQL proficiency (required).
Hands-on expertise with ESPs, notification systems, or CDPs (Iterable, Salesforce, Responsys, Braze, etc.).
Hands-on experience working with APIs, JSON, and event-based data.
Working knowledge of cloud data warehouses (BigQuery, Snowflake) and data governance principles.
Working knowledge of Python for analysis, automation, or workflow orchestration.
Familiarity with streaming or near-real-time systems (Kafka or similar preferred).
Demonstrated success improving campaign performance through technical innovation and automation.
Expert-level proficiency in Google Sheets, including advanced formulas, automation, google apps script, and connected sheets.
Expert-level proficiency in Looker to aid in building reporting dashboards.
Basic knowledge of HTML and CSS
Basic knowledge of Handlebars templating logic
Strong communication and collaboration skills across technical and non-technical partners.

Responsibilities

Data Engineering & Activation Architect, build, and maintain end-to-end activation pipelines across authentication systems (Keycloak), cloud data warehouses (BigQuery, Snowflake), CDPs (Hightouch), and downstream platforms including Iterable, Salesforce, Pushly, Digioh, and Piano.
Own advanced audience modeling, segmentation logic, and personalization frameworks using SQL, APIs, JSON, and event-based data.
Ensure data freshness, accuracy, and reliability to support real-time targeting, lifecycle journeys, and behavioral triggers.
Design and support event-driven and streaming workflows (Kafka or equivalent) to power trigger-based messaging and near-real-time activation.
Serve as the technical authority and escalation point for complex issues involving data syncs, APIs, segmentation logic, templating failures, or platform limitations.
Build and optimize dynamic templates using HTML/CSS and Handlebars logic to power personalized, modular communications at scale.
Develop tooling and automation that reduces manual operational work—monitoring data health, validating segments, triggering campaigns, and logging outcomes.
Partner with ESP and CDP vendors to test and implement new APIs, features, and integration patterns.
Act as a technical escalation point for complex issues involving data syncs, segmentation logic, templating, or API failures.
Act as the hands-on owner and power user of our growth and activation tooling, with deep operational expertise in: Iterable, Pushly, Digioh, Piano, Salesforce, Hightouch, Airtable
Build and maintain front-end messaging components using HTML, CSS, and Handlebars logic to support modular and scalable personalization.
Develop internal tooling and automation to: Monitor data health and pipeline failures Validate audiences and segments Trigger campaigns programmatically Log outcomes and system events
Maintain clean and well-documented runbooks, platform documentation, and architectural diagrams in Confluence.
Track technical work, dependencies, and delivery using Jira, operating comfortably within agile workflows.
Design, build, and experiment with AI-assisted and agentic workflows that automate multi-step operational and analytical tasks, such as extracting data, analyzing results, generating outputs, and distributing deliverables.
Combine tools such as n8n, ChatGPT, Claude, Lovable, Clawdbot, and custom scripts to create: Internal team applications Operational copilots Automated reporting and QA systems
Leverage APIs extensively to connect AI tools with internal data systems, marketing platforms, and productivity tools.
Continuously evaluate emerging AI tooling and frameworks to improve speed, reliability, and scale of growth operations.
Own and build expert-level reporting and dashboarding in Looker and Looker Explore, with a strong emphasis on: Clear, intuitive visual data representations Dashboards tailored to different team functions and levels of technical fluency Reusable explores and metrics that enable self-serve analysis
Partner closely with Data and stakeholders to define trusted metrics, dimensions, and views that align reporting with business outcomes.
Enable analytics workflows that support experimentation, performance measurement, and lifecycle optimization.
Use SQL and Python to analyze engagement, conversion, retention, and operational efficiency.
Build and maintain lightweight reporting layers using Google Sheets and Airtable for fast iteration and stakeholder visibility.
Act as a bridge between Data, Marketing, and Growth teams by translating analytical insights into actionable activation strategies.