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 our analytics platform, continuously identifying opportunities to simplify, standardize, and modernize our Business Intelligence ecosystem.
• Collaborate with DevOps and Software Engineers to improve data ingestion, lineage, orchestration, governance, and platform reliability across the analytics stack.
• Apply AI-assisted development practices to accelerate SQL development, documentation, testing, root cause analysis, and engineering productivity while maintaining rigorous standards for data quality and accuracy.
• Document business definitions, data models, metric logic, and architectural decisions to improve transparency, onboarding, and long-term maintainability.
• Continuously evaluate new technologies, AI capabilities, and analytics engineering practices that improve data quality, governance, developer productivity, and stakeholder confidence.
• Own trusted data products end-to-end—from business discovery and metric definition through implementation, validation, adoption, and continuous improvement.
• Champion a culture of trusted data by helping teams adopt certified data models and reducing duplicate business logic across reports, dashboards, and applications.

 

Who you are

Ownership & Business Impact

• Demonstrated ability to simplify complex data ecosystems by standardizing business logic, establishing trusted metric definitions, reducing duplicate reporting logic, and increasing organizational confidence in data.
• Demonstrated ability to translate ambiguous business problems into trusted, scalable data products by partnering directly with stakeholders throughout discovery, implementation, validation, and adoption.
• Proven track record of independently delivering analytics solutions that improve business decision-making with minimal oversight.
• Strong judgment in evaluating build-vs-buy decisions and identifying opportunities to leverage existing platforms, automation, and AI before creating custom solutions.
• Experience defining business metrics and establishing consistent semantic definitions across multiple stakeholders and reporting systems.

Analytics Engineering Excellence

• Deep experience designing, building, and maintaining certified data models using modern analytics engineering practices.
• Strong understanding of dimensional modeling, semantic layers, data quality, and analytics engineering principles.
• Demonstrated experience implementing automated testing, validation, documentation, and monitoring to improve trust in analytical data.
• Strong systems thinking with the ability to understand how upstream data collection, transformations, and downstream reporting interact across the analytics ecosystem.
• Demonstrated ability to leverage AI-assisted development tools to improve SQL development, documentation, testing, root cause analysis, and engineering productivity while maintaining high standards for accuracy and quality.

Technical Expertise

• Advanced SQL skills with demonstrated experience writing, optimizing, and troubleshooting complex analytical queries.
• Experience with modern data transformation frameworks (e.g., dbt or similar).
• Experience working with cloud data warehouses (e.g., Amazon Redshift, BigQuery, or similar platforms).
• Experience designing data models that balance usability, scalability, performance, and long-term maintainability.
• Familiarity with modern data orchestration, version control, CI/CD, and collaborative engineering workflows.

Collaboration & Communication

• Strong communication skills with the ability to translate technical concepts into business language and collaborate effectively across technical and non-technical stakeholders.
• Self-driven, highly autonomous, and comfortable operating in a remote-first environment while managing priorities and consistently delivering results.
• Passion for building trust in data and continuously improving how organizations measure, understand, and act on business performance.

Experience with Redshift, BigQuery, dbt, Airflow, Dagster, Python, OpenMetadata, semantic layers, or metric stores is preferred, but exact technology matches are not required. This role is best suited for someone who brings a mindset for platform modernization, strong cross-functional partnership, a dedication to data quality and governance, and a practical approach to using AI to accelerate their analytics workflows.

#LI-Remote

*Please note that, as this is a contract position, no perks or benefits are included with this role.

 

Our Analytics Engineering Philosophy at TechnologyAdvice

• We build trusted data — Our goal is simple: every meeting, every dashboard, and every business decision should be powered by the same trusted data. And we believe every business metric should have one trusted definition, not ten competing implementations.
• We think like product engineers — We don't just write SQL. We build reusable data products that solve business problems and improve decision-making across the organization.
• We optimize for trust over speed — Fast dashboards are valuable, but trusted metrics are essential. We invest in testing, documentation, governance, and quality to ensure confidence in every number we publish.
• We embrace AI — We expect the thoughtful use of AI-powered tools (Cursor, Claude, ChatGPT, and others) to accelerate development, documentation, testing, and analysis while maintaining rigorous engineering standards.
• We own outcomes — Analytics Engineers are empowered to challenge assumptions, simplify complexity, improve business definitions, and identify opportunities that increase organizational trust in data.
• We continuously improve — We modernize our analytics platform through automation, standardization, and engineering best practices, always looking for ways to reduce technical debt and increase long-term maintainability.

 

Work authorization

Employer work visa sponsorship and support are not provided for this role. Applicants must be currently authorized to work in India at hire and must maintain authorization to work in India throughout their employment with our company.