TE - 1458 Staff MarTech Engineer

Keka Technologies Private Limited; Hyderabad; On-site; INR 1,500,000 - 2,000,000; Full time

Benefits offered by this job

Training sessions for skill enhancement

Inclusive environment

Reward programs for exceptional performance

Job summary

Keka Technologies Private Limited is seeking a Staff MarTech Engineer to lead their marketing technology and product analytics initiatives. In this role, you will ensure the flow of data from user interactions through various systems, maintain data integrity, and collaborate across engineering, data, and product teams.

With 8-12 years of experience in MarTech engineering, you will own governance for event tracking plans and ensure that the organization’s advertising decisions are data-driven.

The position offers opportunities for personal and professional growth, working in an innovative environment that celebrates diversity.

Qualifications

• 8-12 years in MarTech engineering or product analytics at digital businesses.
• Experience designing event tracking plans across web and server-side events.
• Production experience with analytics tools like Segment and Mixpanel.

Responsibilities

• Own the marketing technology and product analytics stack.
• Ensure data integrity and define governance standards.
• Lead cross-functional alignment and incident response for tracking issues.

Skills

Event tracking governance

Customer Data Platforms (Segment)

Mixpanel analytics

A/B testing

SQL proficiency

Data integrity management

Tools

BigQuery

Mixpanel

Segment

Google Ads

Job description

Staff MarTech Engineer

Time Zone: Must overlap with US working hours

Experience: 8 – 12 years

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 user's 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 modelling. 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.

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 You'll Own

• 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

• 8–12 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.
• 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.
• 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 modelling 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.
• 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 60–70% 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

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.

For more information about our solutions and organization, visit www.softobiz.com ,