Full-Stack Marketer

Nexla, briefly

Nexla is the data connectivity layer for enterprise AI. Over 1,000 bidirectional connectors give agents real-time access to data and actions over MCP. Nexla's Agentic Data Integration handles high-volume streaming ETL, CDC, and Document ETL. At the core of the platform is Helix, a context engine that continuously learns from metadata, schemas, telemetry, and documentation to give agents accurate context and keep pipelines reliable. Nexla processes over a trillion records a month for enterprises including DoorDash, LiveRamp, LinkedIn, and J&J. Honorable Mention in the Gartner Magic Quadrant™ for Data Integration Tools, and top-rated by customers on Gartner Peer Insights four years running.

Role You would own Nexla’s digital presence end to end: SEO, paid, the website funnel, marketing automation, and the content that feeds all of it. The audience is data engineers, IT leaders, and enterprise decision-makers, so the work is as much about understanding data integration as it is about channels. You are part of a global team, which means you set the strategy and then execute it yourself. AI tooling is expected in the work, not treated as a shortcut.

The current marketing team has a technical product marketer role and a web/ brand manager. We use a few agencies to help with paid ad campaigns, website management and creatives for websites and campaigns.

• Organic visibility for data integration and AI keywords. SEO strategy, the technical work behind it, and the content that actually ranks.

• Paid and ABM. Google Ads and LinkedIn Ads from audience targeting through creative, plus the account-based programmes aimed at enterprise prospects.

• The funnel. Website performance and user behaviour, where people drop and why, the marketing automation workflows and lead scoring behind it, and the reporting that says which channel earns more budget and which one stops.

• The content engine. Blogs, whitepapers, case studies, social across LinkedIn and X, video scripts, and webinar material. Technical enough that a data engineer keeps reading, clear enough that the person signing the contract finishes it.

AI tooling runs through all of it: content production, competitive and market research, segmentation, and the triggers behind automated campaigns.

Ninety days in: You would have helped revamp our inbound traffic and conversions to bring in more demo requests and help improve conversion.

The hard problem Most of the traffic today is organic and direct. The hard problem is to make the website an organic lead engine consistently aligning top topics with content needed and SEO/ AEO optimization to drive more qualified traffic and better engagement and conversions. .

Must-haves

• 2 to 5 years in digital marketing, content marketing, or a closely related role, in B2B.

• Hands-on SEO/ AEO, SEM, and web analytics. You have made decisions from Google Analytics, not just reported from it.

• A marketing automation platform such as HubSpot or Marketo, including building the workflows yourself.

• Brand, email and website optimization experience.

• Nice to have - Paid campaign experience on Google Ads and LinkedIn Ads, covering both audience targeting and creative.

• Strong written English and a solid grasp of B2B marketing and enterprise sales cycles.

• You use AI tools in your actual work and can say specifically where they help and where they mislead you.

Bonus points

• SaaS, data technology, or enterprise software marketing, or working knowledge of data integration,