TE 1458 Staff MarTech Engineer

Softobiz

Job Location:

Hyderabad - India

Monthly Salary: Not Disclosed

Posted on: 5 days ago

Vacancies: 1 Vacancy

Job Summary

Job Title: MarTech Engineer

Location: Hyderabad India

Work Model: Full-time

Time Zone: Must overlap with US working hours

Experience: 8 12 years

Staff MarTech Engineer

Product Analytics Growth Platform & Data Integrity

About the Role

We are looking for a Staff MarTech Engineer to own our end-to-end marketing technology and product-analytics stack. You will be the single owner for how events flow from a users first click through onboarding and checkout into our data warehouse our product-analytics tooling and the advertising platforms that drive acquisition.

This is a hands-on individual-contributor role. You will partner daily with engineering data growth and product teams. Success looks like: every conversion captured every experiment measurable every advertising dollar getting accurate feedback and a measurement layer that the whole organisation trusts.

Scope note: this role works closely with the Data Engineering function but does not own warehouse architecture pipelines or data modeling. You consume the warehouse the Data Engineering team builds and maintains it.

Why this role exists the architecture mandate

To strengthen attribution and protect CAC signal quality as the business scales we are investing in system-level design rather than incremental tool configuration.

Specifically: an Edge-based and Server-side conversion architecture (Meta Conversions API Google Enhanced Conversions TikTok Events API Cloudflare Workers at the edge) engineered to perform reliably as browser-side tracking continues to evolve and to keep CAC measurement accurate across ad platforms.

The outcome is a first-party data moat the foundation that lets every ad-spend decision experiment readout and growth bet rest on data the organisation trusts.

What ownership means at the Staff IC level

Ownership in this role means Governance and Truth. You are not a ticket-taker for marketing requests.

You are the single tie-breaker for data integrity. You own the Schema and the Identity Resolution strategy you define the standards that Engineering and Product must follow so that when the business looks at a CAC report everyone in the building trusts the number.

You own the Why behind the data not just the How of the pipeline.

What Youll Own

Schema and Identity Resolution strategy the canonical event schema naming conventions versioning policy and the identity-resolution model (anonymous identified user merge cross-device cross-surface edge-cookie strategy). You define the standards; Engineering and Product implement to them.
Edge and Server-side conversion architecture the system that reduces reliance on browser-side tracking. You design and own the flow where events are captured at the edge (Cloudflare Workers server-side CDP sources) and delivered server-to-server to ad platforms via Meta CAPI Google Enhanced Conversions and TikTok Events API with deduplication against any browser-side mirror.
First-party data moat a measurement foundation that does not depend on third-party cookies pixels or ad-blocker-vulnerable tags. Our CAC attribution and experiment readouts rest on signals you own end-to-end.
Tie-breaker for data integrity when three tools disagree on conversion rate your definition wins. You own the reconciliation model the single source of truth for conversion and CAC and the authority to say this is the number in an exec review.
Customer Data Platform Segment SDKs on web and mobile surfaces server-side sources destination routing and identity stitching. You set the standard for what an event must contain; Engineering implements to it.
Product analytics Mixpanel event registry hygiene funnel / retention / cohort reports session replay and experimentation. You are the registrar and governance owner not a report author.
Conversion APIs end-to-end not just configured endpoints. Event enrichment in the warehouse reverse-ETL out dedup with any client-side mirror match-rate monitoring EMQ optimisation and continuous improvement of ad-platform signal quality.
Experiment design and measurement feature-flag-driven A/B tests for onboarding checkout and pricing flows with clearly defined primary metric guardrails sample-size planning and SRM / peeking discipline.
Pipeline reliability and incident response detect triage and resolve tracking outages (identity-resolution breaks event drops pixel misfires CAPI deliverability regressions).
Cross-functional alignment running the weekly analytics sync with engineering data and growth; unblocking teams by owning the governance decisions no one else can make.

Required Experience

812 years in MarTech engineering product analytics or growth engineering at consumer-facing digital businesses ideally including at least one direct-to-consumer e-commerce or subscription product.
Proven track record designing Edge-based and Server-side conversion architectures not just configuring CAPI endpoints but reasoning about where in the stack each event should originate to maximise match rate perform reliably as browser-tracking signals evolve (ITP ATT ad blockers) and produce a trustworthy CAC signal. Hands-on experience with event deduplication across client server and edge sources is required.
Deep hands-on experience designing and governing event tracking plans across web and server-side events you have authored the schema that other engineers implement to run schema reviews and held the line on data-quality standards when under delivery pressure.
Identity resolution design anonymous identified user merge cross-device and cross-surface stitching edge-cookie strategies for ITP-resistant first-party identity. You have designed this not just consumed it.
Production experience with Segment (or equivalent CDP such as RudderStack or mParticle) SDK integration server-side sources destinations and debugging at the event level.
Production experience with Mixpanel (or Amplitude Heap or equivalent) including event registry governance funnels cohorts and diagnosing data-quality issues end-to-end.
Hands-on production experience with at least one server-to-server conversion pipeline: Meta Conversions API Google Enhanced Conversions TikTok Events API or equivalent including EMQ / match-rate tuning and dedup design.
Hands-on configuring reverse-ETL syncs from the warehouse to ad platforms (Polytomic Hightouch or Census) mapping fields to destination payloads debugging failed syncs and managing audience sync cadence. You configure and operate these tools; warehouse modeling sits with Data Engineering.
Comfortable writing ad-hoc SQL against BigQuery Snowflake or Redshift to validate event data reconcile numbers between analytics tools and build audience definitions working with existing warehouse models rather than building them.
Comfortable reading and writing JavaScript / TypeScript for SDK integration tag implementation and edge workers.
Proven track record running experiments end-to-end hypothesis feature flag instrumentation measurement readout including awareness of statistical gotchas (sample-ratio mismatch peeking sequential testing).
Experience operating during a platform migration re-platforming or a major tracking overhaul you have lived the ambiguity and can bring order to it.

Tools and Technologies

The following stack describes what you will work with day-to-day. You do not need hands-on experience with every single tool depth in 6070% of this list is what we are looking for along with the pattern-matching to learn the rest quickly.

Category	Tools
Customer Data Platform	Segment (required) identity-stitching / user-unification layer server-side sources
Product Analytics	Mixpanel (required) event registry Session Replay Experiments 2.0
Edge & Server-side Architecture	Cloudflare Workers Cloudflare Zaraz Google Tag Gateway server-side tagging
Conversion APIs	Meta Conversions API (CAPI) Google Enhanced Conversions TikTok Events API
Reverse-ETL (configure & operate)	Polytomic (preferred) Hightouch Census
Data Warehouse (consumer)	BigQuery Snowflake or Redshift ad-hoc SQL against existing models
BI / Visualization	Omni Looker Mode Metabase
Experimentation	Mixpanel Experiments 2.0 LaunchDarkly Statsig Optimizely VWO
Session Replay	Mixpanel Session Replay PostHog FullStory
Ad Platforms	Meta Ads Manager Google Ads TikTok Ads
Languages	JavaScript / TypeScript SQL; Python is a plus
Governance & Schema	Segment Protocols Mixpanel Lexicon data contracts PII / consent policy
Collaboration	Linear Slack Google Docs & Sheets Confluence / Notion

Nice to Have

Healthcare fintech or other privacy-sensitive domain experience designing tracking that respects PII / PHI boundaries and withstands compliance review.
Experience as the de-facto data-governance authority at a growth-stage company the person who owns the tracking plan the metric catalog and the definitional authority for what counts as a conversion.
Production experience with Cloudflare Workers Durable Objects Workers KV or Workers Analytics Engine for edge-based tracking and identity.
Experience retiring legacy analytics tooling for example consolidating tag managers migrating session-replay vendors or moving experimentation into a native platform.
Background in privacy / consent engineering: iOS ATT consent management platforms GDPR / DPDP compliance.
Familiarity with dbt and the modern data stack enough to partner with Data Engineering as a peer not a client.
Prior early-MarTech-hire experience at a growth-stage product company.

How You Work

You treat the tracking layer as a product versioned documented reviewed with clear ownership.
You see CAC CVR and retention numbers as contracts not reports. When a number changes you know whether it is signal or system.
You are as comfortable debugging a dropped event in an edge worker as you are explaining an attribution model to senior leadership.
When there is ambiguity about what a metric means you resolve it definitively rather than passing it around. Definitional authority is part of the job.
You prefer one integrated tool over three bolted-together ones but you are pragmatic about migrations and their messy middles.
You partner with engineering rather than throwing tickets over the wall you can read the code that emits the event you are trying to measure.
You bring clarity to ambiguous data you can tell the difference between a real regression and a phantom caused by a system being turned off.
You write things down. The team should not need to re-learn a decision you have already made.

About Softobiz:

Innovation begins with like-minded people aiming to transform the world together. At Softobiz we invite you to become a part of an organization that has been helping clients transform their business by fusing insights creativity and technology. With a team of 350 technology enthusiasts we have been trusted by leading enterprises around the globe for over 18 years.

At Softobiz we foster a culture of equality learning collaboration and creative freedom empowering our employees to grow and excel in their careers. Our technical craftsmen are pioneers in the latest technologies like AI machine learning and product development.

Why Should You Join Softobiz

- Work with technical craftsmen who are pioneers in the latest technologies.

- Access training sessions and skill-enhancement courses for personal and professional growth.

- Be rewarded for exceptional performance and celebrate success through engaging parties.

- Experience a culture that embraces diversity and creates an inclusive environment for all employees.

Softobiz is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will be afforded equal employment opportunities without discrimination based on race creed color national origin sex age disability or marital status.

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Required Experience:

Staff IC

Job Title: MarTech EngineerLocation: Hyderabad IndiaWork Model: Full-timeTime Zone: Must overlap with US working hoursExperience: 8 12 yearsStaff MarTech Engineer Product Analytics Growth Platform & Data Integrity About the Role We are looking for a Staff MarTech Engineer to own our end-to-end mark...