Senior Data Engineer: Scale Pipelines & Snowflake

Heidrick & Struggles; Chicago (IL); On-site; USD 120,000 - 130,000; Full time

Job summary

Heidrick & Struggles is seeking a Senior Data Engineer with 4–5 years of hands-on experience to shape a scalable data foundation in support of the firm’s data‑driven leadership initiatives.

You will own complex data pipelines and data models, mentor junior engineers, and partner with data science, analytics, product, and business stakeholders to deliver trusted analytics and AI capabilities across the organization.

Qualifications

• Bachelor’s degree or equivalent practical experience in a related field.
• 4–5 years building and maintaining data lake/warehouse solutions and pipelines.
• Expert-level SQL with complex queries, optimization, and stored procedures.
• Hands-on Snowflake experience for data modeling and cost management.
• Python for data processing and automation; experience with ETL/ELT.
• Experience mentoring juniors and contributing to technical decisions.
• Solid understanding of data warehousing concepts and data modeling.
• Familiarity with CI/CD practices and Git workflows.

Responsibilities

• Design, develop, and maintain scalable data pipelines and data models.
• Own end‑to‑end data solutions from requirements to deployment and iteration.
• Collaborate with stakeholders to translate business problems into data solutions.
• Promote best practices in data engineering, testing, observability, and CI/CD.
• Mentor junior data engineers through code reviews and guidance.
• Optimize performance, cost, and reliability of Snowflake and pipelines.
• Document data models, data dictionaries, and metadata for governance.
• Implement data capture, ETL/ELT, validation, and automated quality checks.

Skills

SQL proficiency

Snowflake

Python

ETL/ELT pipelines

CI/CD

Education

Bachelor’s degree in Computer Science or related field

Tools

Snowflake

Git-based workflows

FiveTran / data tools

Job description

Heidrick & Struggles is seeking a Senior Data Engineer with 4–5 years of hands-on experience to shape a scalable data foundation in support of the firm’s data‑driven leadership initiatives.

You will own complex data pipelines and data models, mentor junior engineers, and partner with data science, analytics, product, and business stakeholders to deliver trusted analytics and AI capabilities across the organization.