Appnovation

1 week ago

Peer Advocacy and Community Engagement

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Own a discovery-to-scale data pipeline that spots recurring patterns in the field and hands validated solutions to Platform Engineers for enterprise generalization. In a forward-deployed role, design and build data integration and storage systems that enable analytics and AI capabilities. Work autonomously across ambiguity, partnering with multiple teams to prototype end-to-end data applications and improve reliability through SLO/SLI monitoring and post-incident enhancements.

Location: United States

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Manage the discovery-to-scale data pipeline, identifying recurring patterns and delivering validated solutions for enterprise generalization.
•Bridge product building and real-world business problem solving through rapid solution delivery and deep domain immersion.
•Design and build data integration, storage systems, and infrastructure that enable analytics and AI capabilities.
•Define and monitor service level objectives (SLOs/SLIs), driving reliability improvements and post-incident actions.
•Prototype and build end-to-end data applications across diverse technology stacks while managing technical debt.

Key Requirements

•Bachelor’s degree in Computer Science or Engineering with 8–12 years of relevant experience leading complex data engineering projects with multi-team or business impact.
•Design, build, and maintain scalable data pipelines (ETL/ELT) across complex enterprise data landscapes, including handling undocumented schemas.
•Deploy and manage data infrastructure on cloud platforms (AWS, Azure, or GCP), using Infrastructure as Code (Terraform/CloudFormation) and setting up end-to-end CI/CD pipelines.
•Strong conceptual/logical/physical data modeling, balancing normalization, query performance, and safe production schema migrations.
•Design data validation and evaluation frameworks to support deployment and governance of AI/ML models.

Experience:8-12 yearsData engineering

Education:Bachelor's in Computer Science or Engineering

Skills:CommunicationProblem-solvingAccountabilitySystems thinkingCuriosity

Languages:English

Tech Stack:ETLELTAWSAzureGCPTerraformCloudFormationCI/CDSLOsSLIsAI/MLData validationData modeling

Company Brief

Appnovation

Provides digital transformation, design, and engineering services, helping enterprises build customer experiences, digital platforms, and integrations using open-source and cloud technologies across industries.

Industry: Consulting

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Funding: Bootstrapped

Headquarters: Vancouver, Canada

Founded: 2007

Website LinkedIn

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Appnovation

1 week ago

Peer Advocacy and Community Engagement

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Manage the discovery-to-scale data pipeline, identifying recurring patterns and delivering validated solutions for enterprise generalization.
•Bridge product building and real-world business problem solving through rapid solution delivery and deep domain immersion.
•Design and build data integration, storage systems, and infrastructure that enable analytics and AI capabilities.
•Define and monitor service level objectives (SLOs/SLIs), driving reliability improvements and post-incident actions.
•Prototype and build end-to-end data applications across diverse technology stacks while managing technical debt.

Key Requirements

•Bachelor’s degree in Computer Science or Engineering with 8–12 years of relevant experience leading complex data engineering projects with multi-team or business impact.
•Design, build, and maintain scalable data pipelines (ETL/ELT) across complex enterprise data landscapes, including handling undocumented schemas.
•Deploy and manage data infrastructure on cloud platforms (AWS, Azure, or GCP), using Infrastructure as Code (Terraform/CloudFormation) and setting up end-to-end CI/CD pipelines.
•Strong conceptual/logical/physical data modeling, balancing normalization, query performance, and safe production schema migrations.
•Design data validation and evaluation frameworks to support deployment and governance of AI/ML models.

Experience:8-12 yearsData engineering

Education:Bachelor's in Computer Science or Engineering

Skills:CommunicationProblem-solvingAccountabilitySystems thinkingCuriosity

Languages:English

Tech Stack:ETLELTAWSAzureGCPTerraformCloudFormationCI/CDSLOsSLIsAI/MLData validationData modeling

Company Brief

Appnovation

Industry: Consulting

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Funding: Bootstrapped

Headquarters: Vancouver, Canada

Founded: 2007

Website LinkedIn