About the role
structured by ORIGrowth Data Engineer — Email Intelligence & Automation Trademarkia | India | Full-Time Build the world’s best email-intelligence engine for legal services Trademarkia is looking for an unusually resourceful software engineer whose job is simple to describe: Find high-quality, relevant business email opportunities…
What you will do
- Build and operate Trademarkia’s global email-intelligence pipeline.
- Build scrapers, crawlers, API integrations, and ingestion pipelines.
- Maintain deduplication, validation, enrichment, and refresh pipelines.
- Monitor email quality, bounce rates, deliverability, opt-outs, and campaign performance.
- Build attribution and dashboards showing list growth, campaign performance, ROI, and revenue.
What they are looking for
- You do need to be exceptionally good at figuring things out.
- All data collection and outreach must use lawful and authorized sources and comply with applicable privacy, anti-spam, platform, contractual, and opt-out requirements.
Benefits
- Opportunities for incentive compensation tied to measurable results such as qualified pipeline, revenue attribution, data quality, and campaign performance.
Full posting text
Growth Data Engineer — Email Intelligence & Automation Trademarkia | India | Full-Time
Build the world’s best email-intelligence engine for legal services
Trademarkia is looking for an unusually resourceful software engineer whose job is simple to describe:
Find high-quality, relevant business email opportunities around the world, build the systems to capture and enrich that data, and turn it into measurable growth.
Email is one of our highest-ROI acquisition channels.
The problem is that useful data is scattered everywhere: government databases, trademark and patent records, company registries, professional directories, industry events, public websites, APIs, commercial datasets, and other lawful sources.
We want someone whose full-time job is to figure out:
Where is the data?
How do we access it?
How do we structure it?
How do we enrich it?
How do we keep it fresh?
And how do we turn it into campaigns that actually convert?
This is not primarily a marketing job.
It is first a software engineering, data acquisition, automation, and problem-solving role .
The best person for this role will also become excellent at email marketing, analytics, experimentation, and AI-assisted campaign creation.
What you’ll do You will build and operate Trademarkia’s global email-intelligence pipeline.
That may include:
Discovering public and authorized data sources containing business and professional contact information
Building scrapers, crawlers, API integrations, and ingestion pipelines
Extracting structured data from trademark, patent, company, and professional databases
Working across countries including the U.S., Canada, Mexico, the U.K., Europe, India, and others
Identifying newly filed trademarks, new companies, industry participants, event attendees, founders, business owners, and other relevant audiences
Enriching records with useful information such as company, jurisdiction, trademark, filing date, industry, role, and geography
Using APIs and commercial data providers where appropriate
Maintaining deduplication, validation, enrichment, and refresh pipelines
Building systems that continuously identify new records rather than creating one-time lists
Monitoring email quality, bounce rates, deliverability, opt-outs, and campaign performance
Connecting harvested data into CRM and email-marketing systems
Building attribution so we know which sources and campaigns actually produce revenue
Creating dashboards showing list growth, campaign performance, ROI, and revenue
Using AI to generate and test highly personalized email campaigns
Running structured A/B and multivariate experiments
Working directly with attorneys and business teams to understand where valuable data exists
Turning manual research processes into automated pipelines
Example problem Suppose a government trademark database contains information about newly filed trademarks.
Your job is not simply to download the records.
You should be asking:
Can we automatically identify every new filing?
Can we determine the business owner?
Can we lawfully identify a relevant business email?
Can we capture the mark, filing date, owner, country, industry, attorney, and other useful fields?
Can we enrich the record?
Can we identify a relevant service that person may actually need?
Can we automatically place that prospect into the right campaign?
Can we measure whether the resulting campaign generated revenue?
Then build the entire pipeline.
You will work like an engineer, not a list builder We are looking for someone who can write production-quality systems.
You should be comfortable with areas such as:
Python, Go, JavaScript/TypeScript, or similar languages
Web scraping and crawling
Playwright, Selenium, Puppeteer, Scrapy, or similar tools
REST APIs
HTML parsing
Data extraction and normalization
PostgreSQL or similar databases
Data pipelines and queues
Cloud infrastructure
Scheduled jobs and monitoring
Proxies and distributed crawling where lawful and appropriate
Data enrichment APIs
Email validation
CRM integrations
Analytics and attribution
AI APIs and agentic workflows
You do not need to know every tool on day one.
You do need to be exceptionally good at figuring things out.
AI is part of the job Once the data pipeline is working, AI makes the rest far more powerful.
You will use tools such as Claude, ChatGPT, and other AI systems to help:
Research audiences
Understand what a prospect may need
Segment lists
Personalize outreach
Generate multiple campaign variants
Write subject lines
Test positioning
Analyze results
Identify patterns in conversion
Improve campaigns continuously
We do not want someone manually writing one email campaign every few weeks.
We want someone who can build a system capable of testing dozens of ideas rapidly and learning from the data.
Think globally Trademarkia serves clients around the world.
A major part of this role is discovering data sources other people overlook.
For example:
A trademark registry in Mexico.
A company database in Canada.
A state business database in California or Arizona.
A patent or PCT dataset.
An industry conference.
A professional association.
A startup event.
A government licensing database.
A commercial dataset.
A public directory.
Your instinct should be:
“There are valuable prospects here. How do I turn this into a clean, continuously refreshed dataset?”
Then you build it.
How you’ll be measured This role has very clear outcomes.
Every month, we should be able to answer:
How many useful new contacts did you discover?
Where did they come from?
How accurate is the data?
How many were reached?
What were the bounce and unsubscribe rates?
What campaigns performed best?
How many qualified leads resulted?
How much revenue did those campaigns generate?
What will you build next month?
We expect this role to become increasingly performance-driven, with opportunities for incentive compensation tied to measurable results such as qualified pipeline, revenue attribution, data quality, and campaign performance.
Who should apply This role is for someone unusually resourceful.
You may be a great fit if you are:
A strong software engineer who enjoys unusual data problems
Someone who builds scripts rather than doing repetitive work manually
Obsessed with automation
Comfortable exploring unfamiliar websites and systems
Strong at reverse-engineering workflows
Curious about how data is structured
Comfortable dealing with messy real-world datasets
Analytical enough to measure what actually works
Creative enough to find sources nobody else has considered
Excited by the combination of engineering, AI, growth, and data
We care much more about what you can build than your job title.
Strong computer science fundamentals matter.
Resourcefulness matters more.
This is not a traditional marketing role We are not primarily looking for a copywriter, SEO specialist, social media manager, or conventional performance marketer.
We are looking for an engineer who thinks:
“Give me the target audience. I will figure out where the data lives, build the pipeline, enrich it, automate it, and measure the result.”
Over time, you should also become excellent at email marketing and growth analytics.
Responsible data use All data collection and outreach must use lawful and authorized sources and comply with applicable privacy, anti-spam, platform, contractual, and opt-out requirements.
Part of being excellent at this job is knowing how to build powerful data systems responsibly.
Location India — Full-Time
We are particularly interested in strong engineers in Bengaluru, Chennai, Hyderabad, Pune, Nagpur, and other major engineering hubs , as well as exceptional candidates from institutions such as VIT and similar universities.
Why this role matters Most companies treat prospecting as a marketing task.
We think it is increasingly an engineering problem .
The engineer who can continually discover the right data, structure it, enrich it, connect it to AI, and measure the resulting revenue can create enormous value.
That is the person we want.
How to apply Send us:
Your resume
GitHub or examples of systems you have built
A short explanation of the most difficult scraping, crawling, automation, or data-pipeline problem you have solved
One example of a public or commercially available dataset you think Trademarkia should be using—and what you would build with it
Bonus: Show us a small working prototype.
We value people who build first and explain second.
Seniority level: Entry level
Employment type: Full-time
Industries: Business Consulting and Services