Sr. AI Data Engineer

We Love AI Jobs; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

We Love AI Jobs is seeking a Senior AI Data Engineer in Bangalore to build and operate verified data capabilities for analytics and AI. You will develop and optimize data pipelines, data models, and governance across Data Concierge and AskInsights, collaborating with data science, governance, and business teams.

You will drive reliability, production support, and scalable data infrastructure, using dbt, SQL, and Alteryx, while advancing enterprise data products and integrations.

Qualifications

• 4–6 years of relevant professional experience in Data Engineering or analytics.
• Strong hands-on experience building production-grade data pipelines.
• Strong SQL proficiency and experience with dbt.

Responsibilities

• Own ongoing support, maintenance, reliability, and enhancement of Data Concierge and AskInsights.
• Build, test, deploy, and optimize data pipelines and transformations using dbt, SQL, Alteryx.
• Design and develop governed, reusable data models and contextual data capabilities.
• Monitor data and application health; troubleshoot production issues.
• Implement automated testing, data-quality controls, observability, and deployment practices.

Skills

SQL

dbt

Alteryx

Data Pipelines

Data Modeling

APIs

CI/CD

Observability

Job description

# Sr. AI Data EngineerAlteryxBangalore, IndiaFull-timeUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageThe Senior AI Data Engineer builds and supports data pipelines, models, and governed data capabilities for analytics and AI use cases. The role also owns the reliability and improvement of AI-powered products such as Data Concierge and AskInsights, working with engineering, data science, governance, and business teams.* Permanent* 4–6 years### Skills and expertiseSQLdbtAlteryxData pipelinesData modelingAPIsCI/CDObservability### Key responsibilities* Maintain and improve the reliability of Data Concierge, AskInsights, and related AI-powered products.* Build, test, deploy, and optimize data pipelines and transformations using dbt, SQL, and Alteryx.* Develop governed data models and implement testing, monitoring, and data-quality controls.## How this job comparesCompared with 269 open senior data jobs on October 10, 2026.Similar open jobs: We Love AI Jobs lists 269 open senior data jobs at 124 companies.Remote work: This job is on site. 60 of the 269 senior data jobs (22%) are remote.AI in this role: Medium. The role uses AI tools and works with AI systems as a regular part of the job. The role supports AI-powered data products and builds contextual data capabilities for AI use cases, including integrations with AI services. Its work also covers broader data engineering, production support, and analytics pipelines.## Full descriptionMeet the Moment with AlteryxWe'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.