DBT Data Engineer; hybrid

Job Title and Location

DBT Data Engineer (hybrid) – King of Prussia, Pennsylvania, United States.

The DBT SME serves as the senior engineer for data transformation within a modern data stack built on dbt and Snowflake. This role is responsible for implementing dbt transformation models, enforcing modeling best practices, and ensuring that dbt and traditional data modeling disciplines work together cohesively in production. The ideal candidate brings hands‑on dbt expertise, deep Snowflake knowledge, strong Python skills, and the ability to translate conventional data warehouse patterns into maintainable, scalable dbt solutions.

• Design and develop dbt transformation models targeting Snowflake, applying model layering (staging, intermediate, mart), incremental strategies, snapshot patterns, and dbt macros.
• Apply Snowflake‑specific optimizations within dbt models, including clustering keys, transient tables, and appropriate warehouse sizing to control cost and performance.
• Translate traditional data warehouse designs—including dimensional models, ERDs, and legacy SQL transformation logic—into dbt‑native patterns.
• Develop and maintain dbt tests (generic and singular), custom Python‑based data quality checks, and documentation to ensure transformation correctness and pipeline observability.
• Perform peer code reviews, provide technical mentorship to engineers, and drive adoption of dbt best practices and modeling standards across the team.
• Troubleshoot data discrepancies, pipeline failures, and Snowflake query performance issues, and implement preventive measures.
• Maintain technical documentation, transformation runbooks, and handover materials.

• 5+ years of DBT Core experience—including model layering, macros, Jinja templating, incremental materializations, snapshots, and dbt tests.
• 3+ years of hands‑on Snowflake experience as a dbt target, including SQL dialect proficiency, query optimization, clustering, and RBAC.
• 3+ years of Python experience applied to data engineering, including pipeline scripting, automation, and data quality tooling.
• 5+ years of SQL experience—including complex joins, window functions, CTEs, and aggregations across large datasets.

Where required by law, NTT DATA provides a reasonable range of compensation for specific roles. The starting pay range for this hybrid role is $100,000 – $125,000. This range reflects the minimum and maximum target compensation for the position across all U.S. locations. Actual compensation will depend on a number of factors, including the candidate’s actual work location, relevant experience, technical skills, and other qualifications.

This position may also be eligible for incentive compensation based on individual and/or company performance.

Benefits include medical, dental, and vision insurance with an employer contribution, flexible spending or health savings account, life and AD&D insurance, short and long‑term disability coverage, paid time off, employee assistance, 401(k) program with company match, and additional voluntary or legally‑required benefits.

NTT DATA is an equal‑opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For more information about your EEO rights under the law, please . For Pay Transparency information, please .

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