Senior Big Data Engineer - Hybrid Cloud Data Platform Lead

Sapient Corporation; Chicago (IL); Hybrid; USD 136,000 - 160,000; Full time

Benefits offered by this job

Competitive compensation

Work-life balance

Health benefits

Wellness program

Paid leave

Job summary

Publicis Sapient in Chicago is seeking a Senior Associate Data Engineer to design, develop, and maintain scalable Big Data solutions in a hybrid work setting, partnering with clients to translate requirements into data platforms and modern pipelines.

You will own end-to-end data pipelines, collaborate across roles, and mentor junior engineers while delivering production-grade data platforms on AWS/Azure/GCP, Databricks, and lakehouse patterns.

Qualifications

• Experience building end-to-end data pipelines and production-grade data platforms.
• Hands-on with at least one leading cloud data platform (AWS/Azure/GCP).
• Databricks experience including notebooks, jobs, and lakehouse patterns.
• Strong Python for data engineering and AI workflows.
• Experience with BigQuery, Redshift, Vertica, Cosmos DB, DynamoDB, or similar databases.

Responsibilities

• Design, develop and deliver large-scale data systems and modernization initiatives.
• Build and optimize batch and streaming data pipelines on cloud platforms.
• Mentor junior team members and contribute hands-on to delivery.
• Automate data platform operations and ensure observability and reliability.
• Provide project estimates and feasibility assessments.

Skills

End-to-end data pipelines

Public cloud platforms

Databricks

Python

Data modeling & warehouse

CI/CD & production support

MLOps concepts

Communication & collaboration

Tools

Databricks

Snowflake/BigQuery/Redshift

SQL/NoSQL databases

Spark

CI/CD tooling

Job description

Publicis Sapient in Chicago is seeking a Senior Associate Data Engineer to design, develop, and maintain scalable Big Data solutions in a hybrid work setting, partnering with clients to translate requirements into data platforms and modern pipelines.

You will own end-to-end data pipelines, collaborate across roles, and mentor junior engineers while delivering production-grade data platforms on AWS/Azure/GCP, Databricks, and lakehouse patterns.