Sr. Data Engineer

Experis; Appleton (WI); Hybrid; USD 110.000 - 160.000; Vollzeit

Benefits dieser Stelle

Medical and Prescription Drug Plans

Dental Plan

Vision Plan

Health Savings Account

Health Flexible Spending Account

Dependent Care Flexible Spending Plan

Life Insurance

Disability Insurance

Business Travel Insurance

401(k), Plus Match

Weekly Pay

Zusammenfassung

Experis in the United States is seeking a Senior Data Engineer to own and deliver governed data pipelines on Snowflake and Azure, shaping ingestion, transformation, and serving layers for leadership reporting and AI capabilities.

You will set patterns for data governance, model scalability, and reliability, while mentoring engineers and aligning with the Director, Data & Analytics on strategy. This hybrid role is based in Appleton, WI.

Qualifikationen

• 4 to 7 years of professional data engineering experience with enterprise-grade platforms.
• Advanced SQL skills including performance tuning and schema design at scale.
• Hands-on experience with dbt or an equivalent transformation framework including testing, documentation, and CI/CD integration.
• Production experience with Snowflake and strong working knowledge of Microsoft Azure data services (ADF, SQL, Storage, Key Vault).
• Knowledge of data governance, lineage, cataloging, and security/compliance practices including SOC 2 Type 2 and PII handling.

Aufgaben

• Lead the design and implementation of governed, production-ready data pipelines on Snowflake and Azure, owning ingestion, transformation, and serving layers.
• Architect ingestion and integration patterns across source systems using CDC, batch, and streaming approaches.
• Establish transformation frameworks with dbt as the modeling standard, ensuring pipelines are version-controlled, tested, and observable.
• Own pipeline SLAs by defining targets for freshness, completeness, and error-rate with documented runbooks and on-call readiness.
• Drive schema governance, data modeling discipline, and data lineage/metadata management for traceable KPIs with clear stewardship.
• Partner with the Director, Data & Analytics on platform strategy, roadmap, and the Center of Excellence operating model.
• Mentor Data Engineers through code reviews, architectural pairing, and knowledge sharing as the team scales.

Kenntnisse

SQL

Data leadership

CI/CD

Tools

dbt

Snowflake

Azure Data Factory

Azure SQL

Storage

Key Vault

Jobbeschreibung

The Sr. Data Engineer role supports a Data & Analytics organization and the Data Foundation team, with ownership of governed, production-ready pipeline design and delivery across Snowflake and Azure.

Role Focus

Serve as a technical leader for enterprise-grade data pipeline engineering. Own the ingestion, transformation, and serving layers for governed data products, establishing patterns and standards that enable reliable delivery of data used for leadership reporting and AI-powered capabilities.

Responsibilities

• Lead the design and implementation of governed, production-ready data pipelines on Snowflake and Azure, owning ingestion, transformation, and serving layers.
• Architect ingestion and integration patterns across source systems, applying CDC, batch, and streaming approaches when appropriate.
• Establish transformation frameworks using dbt as the modeling standard, ensuring pipelines are version-controlled, tested, and observable.
• Own pipeline SLAs by defining and tracking targets for freshness, completeness, and error-rate, with documented runbooks and production on-call readiness.
• Drive schema governance, data modeling discipline, and data lineage/metadata management so governed KPIs have traceable sources and clear stewardship.
• Partner with the Director, Data & Analytics on platform strategy, roadmap, and the Center of Excellence operating model.
• Mentor Data Engineers through code review, architectural pairing, and knowledge sharing as the team scales.

Required Qualifications

• 4 to 7 years of professional data engineering experience, including demonstrated technical leadership on enterprise-grade data platforms.
• Advanced SQL skills, including complex query authorship, performance tuning, and schema design at scale.
• Hands-on experience with dbt (preferred) or an equivalent transformation framework, including testing, documentation, and CI/CD integration.
• Production experience with Snowflake and strong working knowledge of Microsoft Azure data services, including Azure Data Factory, Azure SQL, Storage, and Key Vault.
• Working knowledge of data governance, lineage, cataloging, and security/compliance practices in regulated environments, including SOC 2 Type 2 and PII handling principles.

Technology Stack

• Snowflake
• Azure
• dbt
• SQL
• CDC
• Azure Data Factory
• Azure SQL
• Storage
• Key Vault
• SOC 2 Type 2

Work Location

Appleton, WI (hybrid). Minimum experience: 4 years.

Benefits

• Medical and Prescription Drug Plans
• Dental Plan
• Vision Plan
• Health Savings Account
• Health Flexible Spending Account
• Dependent Care Flexible Spending Account
• Supplemental Life Insurance
• Short Term and Long Term Disability Insurance
• Business Travel Insurance
• 401(k), Plus Match
• Weekly Pay

Benefits Eligibility After Waiting Period Completion

Upon completion of the waiting period, consultants are eligible for the following: Medical and Prescription Drug Plans, Dental Plan, Vision Plan, Health Savings Account, Health Flexible Spending Account, Dependent Care Flexible Spending Account, Supplemental Life Insurance, Short Term and Long Term Disability Insurance, Business Travel Insurance, 401(k), Plus Match, and Weekly Pay.

What's Included in the Role

• Opportunity to architect and operate a governed Snowflake + Azure-native data foundation supporting leadership reporting and AI-powered capabilities.
• Work within an AI governance framework developed in partnership with the client's Legal, InfoSec, Privacy, and Compliance teams to support responsible AI deployment.
• Use AI development assistants as part of daily engineering practice, including GitHub Copilot, Microsoft Copilot, Claude, and emerging agent-based tooling.