Senior Analytics Engineer (Contract)
TechnologyAdvice
| Company | TechnologyAdvice |
| Category | Engineering |
| Location | India - Remote |
| Remote | Remote |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 13 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Hi, we're TechnologyAdvice.
Headquartered in Nashville, Tennessee, TechnologyAdvice helps millions of B2B technology buyers make smarter decisions by providing trusted research, practical guidance, and connections to the world's leading technology brands. Our work spans 30+ media brands and 50+ newsletters, supported by a global team across the United States, United Kingdom, Singapore, Australia, and the Philippines.
We're a remote-first company that values curiosity, collaboration, and growth. We invest in our people, embrace AI and new technologies to improve how we work, and create opportunities for team members to build meaningful careers. Many of our leaders have grown from within, including our CEO, who started here as an intern.
We believe great work happens when people feel connected. Through company all-hands, team events, Slack communities, learning sessions, and in-person gatherings, we create intentional opportunities for our global team to collaborate, build relationships, and celebrate successes together.
All positions are open to remote work unless otherwise specified in the requirements below. The opportunity
We're seeking a Senior Analytics Engineer who views data as a product and trusted business data as a strategic asset. You'll partner closely with Engineering, Finance, Revenue, Marketing, Editorial, and other business teams to build the certified data models, semantic layers, and analytics platform that enable confident decision-making across TechnologyAdvice.
As an individual contributor on our distributed team, you'll independently identify opportunities to improve how data is collected, modeled, validated, documented, and consumed throughout the organization. You'll own initiatives from discovery and business definition through implementation, testing, documentation, adoption, and ongoing iteration—working directly with stakeholders to establish trusted metrics and eliminate ambiguity in how the business measures success.
We're rebuilding the foundation of how trusted data is created, governed, and consumed across TechnologyAdvice. Success in this role isn't measured by the number of dashboards built or SQL queries written. It's measured by the trust the organization places in its data, the adoption of certified data models, improvements in decision-making, and your ability to independently identify and deliver high-value opportunities that improve how the company operates.
The best candidates are naturally curious, highly autonomous, and enjoy translating ambiguous business problems into scalable, trusted data products. They leverage modern AI tools to accelerate development, documentation, testing, and analysis while maintaining rigorous standards for data quality, governance, and engineering excellence.
Our goal is simple: every meeting, every dashboard, and every business decision should be powered by the same trusted data.
If you're excited by the opportunity to help build a modern analytics platform where every meeting can rely on the same trusted metrics, we'd love to talk.
Location : India (Remote)
Employment Type : Contractor
What you'll do
Own the design, implementation, and evolution of certified data models, semantic layers, and trusted business metrics that become the foundation for reporting and decision-making across TechnologyAdvice.
Partner directly with Finance, Revenue, Marketing, Editorial, Product, and Engineering stakeholders to understand business questions, define trusted metric definitions, and translate ambiguity into scalable data solutions.
Design, build, and maintain analytics models, transformations, and data products using modern analytics engineering practices.
Establish and continuously improve data quality through automated testing, validation, monitoring, and observability to ensure business stakeholders can trust the data they use every day.
Improve the architecture, organization, and maintainability of ou
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