Job description

Employment Eligibility Statement: Due to specific project and client requirements, this position is open to U.S. Citizens and U.S. Lawful Permanent Residents (Green Card holders). Sponsorship is not available at this time. Danta Technologies evaluates all candidates in compliance with the Immigration and Nationality Act (INA) and EEOC guidelines. All hiring decisions are made without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic Customer Industry: Financial services industry, specifically spanning insurance, banking, and investment/retirement solutions Job Description: We have a strategic opportunity within EDAO to build and implement AI-assisted engineering capabilities across 31 production dbt projects in the Marketing Analytics portfolio. The initiative will integrate GitHub Copilot with dbt, Snowflake, GitLab, Jira, Confluence, dbt Cloud, and CTM workflows to accelerate delivery while maintaining governance and human oversight. Key Responsibilities • Design and build reusable AI skills, prompts, agents, and instruction files for dbt and data engineering workflows. • Develop AI capabilities for Jira story intake, impact analysis, technical design, dbt model generation, testing, and code review. • Build automation for CTM configuration validation, dependency sequencing, scheduling alignment, and deployment-readiness checks. • Develop deployment skills covering GitLab merge requests, CI/CD pipelines, dbt Cloud execution, release runbooks, and change evidence. • Build automated regression-testing and data-reconciliation capabilities across development, pre-production, and production environments. • Apply strong hands-on knowledge of dbt models, macros, materializations, incremental strategies, tests, documentation, lineage, and dbt Fusion. • Use Snowflake metadata, dbt manifests, GitLab repositories, and lineage information to identify upstream and downstream change impacts. • Develop Python-based automation for API integration, metadata processing, validation, structured outputs, and workflow orchestration. • Create reusable engineering standards for SQL, dbt, testing, data modeling, error handling, observability, and repository structure. • Build AI-assisted support for pipeline monitoring, data freshness, anomaly analysis, defect investigation, and production reconciliation. • Integrate AI-assisted workflows with GitHub Copilot, Jira, Confluence, GitLab, Snowflake, dbt Cloud, CTM, and approved MCP servers. • Create golden datasets and evaluation scenarios to measure AI-draft acceptance, accuracy, rework, test coverage, and edge-case handling. • Review AI-generated artifacts for business-logic accuracy, maintainability, security, performance, and compliance with project standards. • Support pilot implementation, developer enablement, troubleshooting, and scaled adoption across the dbt project estate. • Collaborate with developers, technical leads, architects, QA teams, platform teams, and deployment stakeholders throughout the lifecycle. Skill Requirements • Skill set: DBT, Snowflake, Python, and AI • Finance experience is mandatory Other Requirements: The selected resources will contribute to AI-driven engineering solutions covering requirements analysis, impact assessment, development, automated testing, deployment orchestration, reconciliation, and production support. Notes :- All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance. Benefits : Danta offers a compensation package to all W2 employees that are competitive in the industry. It consists of competitive pay, the option to elect healthcare insurance (Dental, Medical, Vision), Major holidays and Paid sick leave as per state law. The rate/ Salary range is dependent on numerous factors including Qualification, Experience and Location.

Requirements

Must-haves

Due to specific project and client requirements, this position is open to U.S. Citizens and U.S. Lawful Permanent Residents (Green Card holders). Sponsorship is not available at this time.
Customer Industry: Financial services industry, specifically spanning insurance, banking, and investment/retirement solutions
Design and build reusable AI skills, prompts, agents, and instruction files for dbt and data engineering workflows.
Develop AI capabilities for Jira story intake, impact analysis, technical design, dbt model generation, testing, and code review.
Build automation for CTM configuration validation, dependency sequencing, scheduling alignment, and deployment-readiness checks.
Develop deployment skills covering GitLab merge requests, CI/CD pipelines, dbt Cloud execution, release runbooks, and change evidence.
Build automated regression-testing and data-reconciliation capabilities across development, pre-production, and production environments.
Apply strong hands-on knowledge of dbt models, macros, materializations, incremental strategies, tests, documentation, lineage, and dbt Fusion.
Use Snowflake metadata, dbt manifests, GitLab repositories, and lineage information to identify upstream and downstream change impacts.
Develop Python-based automation for API integration, metadata processing, validation, structured outputs, and workflow orchestration.
Create reusable engineering standards for SQL, dbt, testing, data modeling, error handling, observability, and repository structure.
Build AI-assisted support for pipeline monitoring, data freshness, anomaly analysis, defect investigation, and production reconciliation.
Integrate AI-assisted workflows with GitHub Copilot, Jira, Confluence, GitLab, Snowflake, dbt Cloud, CTM, and approved MCP servers.
Create golden datasets and evaluation scenarios to measure AI-draft acceptance, accuracy, rework, test coverage, and edge-case handling.
Review AI-generated artifacts for business-logic accuracy, maintainability, security, performance, and compliance with project standards.
Support pilot implementation, developer enablement, troubleshooting, and scaled adoption across the dbt project estate.
Collaborate with developers, technical leads, architects, QA teams, platform teams, and deployment stakeholders throughout the lifecycle.
Skill Requirements
Skill set: DBT, Snowflake, Python, and AI
Finance experience is mandatory

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aijiraci/cdpythonapisql

Platform: jobdiva
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision