Marketing Automation Engineer

inKind•Austin, TX

1d•Onsite

About The Position

At inKind, we’re building a new way to drive customers to restaurants. We power the relationship between millions of users and thousands of restaurants. We are looking for a Marketing Automation Engineer at inKind who can optimize the consumer relationship with a mix of marketing best-practices, strong understanding of data flow, and the ability to translate it to genuine personalization while technically executing on them at scale. You’ll collaborate closely with business and marketing teams to build systems that directly impact the restaurants and users who rely on inKind. As a Marketing Automation Engineer at inKind, you will be responsible for implementing marketing campaigns. You will receive creative briefs and project plans, and be responsible for drafting technical implementation docs and building them. Much of this building will be done dashboard-side in Braze Canvases. Optimizing platform usage, data-based triggering, and understanding user journeys are all key aspects of this role. Our team has a builder-first mindset, leveraging modern Consumer Engagement Platform (CEP) tools such as Braze and data warehouses like Snowflake, to power rich datasets of user information to use for personalization and customer lifecycle management. We are looking for someone who can turn that data into dynamic, well-timed, high-relevance communication across email, SMS, and push — at scale. This role would have the opportunity to create genuine personalization engines using best-in-class tooling and data models.

Requirements

4+ years of experience with a major CEP/CRM or marketing automation platform (Braze, Shopify, Iterable, Klaviyo, or equivalent)
2+ years of experience with Braze
Deep expertise in journey/canvas building — multi-step, behavior-triggered flows with branching logic, delays, and channel mixing
Dynamic templating skills: conditional blocks, variable logic, and live data integrations
Experience with audience segmentation using behavioral data, custom attributes, and event properties
Solid understanding of contact data models — user profiles, identified vs. anonymous users, subscription and consent management
Ability to read API responses and event payloads to self-diagnose data issues without engineering support
Liquid code proficiency
Deep understanding of email deliverability fundamentals: list hygiene, bounce handling, unsubscribe management, and sender reputation
Understanding of email domains/behavior and record management
SMS compliance knowledge: opt-in/opt-out mechanics, quiet hours, carrier filtering, and message encoding
Familiarity with TCR rules and regulations

Nice To Haves

SQL proficiency and experience working with a cloud data warehouse (Snowflake, Redshift, or BigQuery) for CRM analytics or audience building
Background in consumer apps, marketplaces, or loyalty/rewards programs where lifecycle marketing directly drives repeat behavior
Familiarity with how CRM data flows from a backend application via REST API or event streaming
Experience with in-app messaging, content cards, or push notification strategy beyond transactional sends

Responsibilities

Architect and build complex journey flows - multi-branch, behavior-triggered, time-delayed - that respond dynamically to what users do in the app
Create sophisticated email, SMS, and push templates using dynamic templating (in Liquid): conditional content blocks, personalized variables, abort conditions, and live data pulls
Manage subscription and compliance workflows for SMS opt-in/opt-out, email unsubscribe, and push permission states and follow TCR regulations
QA (Verify) every campaign before launch and own responsibility post-launch: audience spot-checks, template rendering validation, link tracking, SMS encoding, and cross-client email rendering
Translate high-level marketing briefs into well-defined audience definitions, validating logic against actual user data before launch
Understand CEP best practices to inform cadence of messaging, frequency capping, and prioritizing of marketing communications across lifecycle and ad-hoc campaigns
Write, understand, and document Liquid code to build dynamic content blocks
Query our data warehouse (Snowflake) using SQL or review API payloads to validate that events and attributes match expected values, QA before launch, as well as triage potential issues.
Use platform-native diagnostic tools (message logs, user lookup, event streams) to diagnose issues without needing an engineer to triage alongside you
Understand technical limitations of campaigns and recommend well-scoped solutions
Build precise, multi-condition audience segments using a full range of segmentation capabilities
Maintain a clean, documented segment library — consolidating redundant definitions and flagging when underlying data changes affect targeting
Partner with the cross-functional teams to define and action on lifecycle stages (active, lapsing, high-value, etc.) and build reusable and trackable segments that reflect those definitions reliably
Build and maintain a reusable component library: shared content blocks, brand-compliant modules, and snippet logic the team can use without rebuilding from scratch