Sr. AI Data Engineer
Alteryx Bengaluru, Karnataka, India
Software Development · 1,001-5,000 employees
About the role
The Senior AI Data Engineer will own the reliability and enhancement of AI-powered data products like Data Concierge and AskInsights. They will also design, build, and optimize scalable data pipelines and models while ensuring data quality and governance across enterprise systems.
What they look for
Requirements
Candidates must have 4–6 years of professional experience in data engineering or a related technical field. Proficiency in SQL, dbt, and Alteryx is required, along with a strong understanding of data modeling and production-grade data pipeline support.
Full description
Meet the Moment with Alteryx
We're living through a once-in-a-generation shift in how work gets done. Data, automation, and AI are quickly becoming the center of every business decision - and Alteryx is leading the transformation.
You'll be working on the challenges that sit at the heart of modern business. No matter your role, the work you do will help organizations move faster, see more clearly, and tackle questions that used to feel impossible.
If you're ready to meet the moment with innovation, curiosity, and excellence, there's a place for you here.
The Senior AI Data Engineer builds and operates trusted data capabilities that support enterprise analytics and AI. This role owns the reliability and continuous improvement of key AI-powered data products, including Data Concierge and AskInsights, while also developing and optimizing data pipelines and models using dbt, SQL, and Alteryx.
Working across Data Engineering, Data Science, Governance, and business-aligned data teams, this role turns emerging AI use cases and traditional data requirements into secure, scalable, and reusable enterprise capabilities.
Core Competencies:
- Data Engineering: Design and build maintainable data pipelines, transformations, and data models using modern data-engineering practices.
- Production Ownership: Proactively monitor, support, troubleshoot, and continuously improve business-critical data and AI products.
- AI Systems Understanding: Understand how enterprise data, semantic context, data models, APIs, and application components come together to enable reliable AI-powered experiences.
- Technical Problem-Solving: Diagnose complex data, performance, integration, and production issues and implement durable solutions.
- Data Quality & Reliability: Build appropriate testing, monitoring, observability, and governance into data products.
- Collaboration: Work effectively across technical and business teams while reinforcing shared engineering standards and ownership.
Key Responsibilities:
- Own the ongoing support, maintenance, reliability, and enhancement of Data Concierge, AskInsights, and related AI-powered data products.
- Build, test, deploy, and optimize data pipelines and transformations using dbt, SQL, Alteryx, and related technologies.
- Design and develop governed, reusable data models and contextual data capabilities that support analytics, automation, and AI use cases.
- Monitor data and application health, troubleshoot production issues, perform root-cause analysis, and improve reliability, performance, scalability, and cost efficiency.
- Implement automated testing, data-quality controls, observability, documentation, and deployment practices across data products and pipelines.
- Build and maintain integrations with enterprise platforms, APIs, data sources, and AI services as required.
- Partner with Data Engineering, Data Science, Governance, Customer 0, and embedded Data Ops teams to deliver reusable enterprise data products.
- Translate business and AI requirements into scalable technical solutions while maintaining appropriate governance and security standards.
- Evaluate emerging AI and data-engineering technologies and capabilities and apply them where they provide practical enterprise value.
- Contribute to engineering standards, reusable patterns, documentation, and best practices across the broader data organization.
Qualifications & Experience:
- 4–6 years of relevant professional experience in Data Engineering, Analytics Engineering, or a closely related technical role.
- Strong hands-on experience building and supporting production-grade data pipelines, transformations, and data models.
- Strong proficiency in SQL and practical experience working with modern data transformation frameworks such as dbt.
- Experience with Alteryx or similar data preparation, analytics, or workflow automation platforms.
- Experience designing and maintaining data solutions within cloud-based or modern enterprise data environments.
- Good understanding of data modeling, data quality, testing, monitoring, observability, and production support.
- Experience integrating data solutions with APIs, enterprise applications, and external services.
- Understanding of software engineering practices such as version control, CI/CD, automated testing, and deployment processes.
- Exposure to AI/ML, Generative AI, LLM-powered applications, semantic layers, or AI-enabled data products is highly desirable.
- Ability to troubleshoot complex data and integration issues and drive them through to resolution.
- Strong communication and collaboration skills with the ability to work across engineering, data science, governance, and business teams.
Find yourself checking a lot of these boxes but doubting whether you should apply? At Alteryx, we support a growth mindset for our associates through all stages of their careers. If you meet some of the requirements and you share our values, we encourage you to apply. As part of our ongoing commitment to a diverse, equitable, and inclusive workplace, we’re invested in building teams with a wide variety of backgrounds, identities, and experiences.
This position involves access to software/technology that is subject to U.S. export controls. Any job offer made will be contingent upon the applicant’s capacity to serve in compliance with U.S. export controls.
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