Trademarkia
Website:
trademarkia.com
Job details:
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.
Click on Apply to know more.