Lead Big Data Architect — Hybrid Chicago

Sapient Corporation; Chicago (IL); Hybrid; USD 135,000 - 190,000; Full time

Benefits offered by this job

Inclusive workplace

Learning & development opportunities

Competitive compensation and benefits

Flexible work arrangements

Health benefits for you and family

Generous paid leave

Job summary

Publicis Sapient in Chicago is seeking a Manager Big Data Engineering to lead design and delivery of scalable data platforms. You will steer cross-functional teams, translate client requirements into robust data solutions, and drive modernization across batch and streaming pipelines.

The role emphasizes strong cloud experience, Python and data modeling, with a focus on AI-enabled use cases, observability, and production operations.

Qualifications

• Experience implementing end-to-end data pipelines and production-grade platforms.
• Hands-on with leading cloud data platforms (AWS, Azure, GCP).
• Strong Python proficiency for data engineering and AI workflows.
• Familiarity with MLOps concepts and data engineering for AI/ML deployments.
• Ability to work in cross-functional, client-facing consulting environments.

Responsibilities

• Design and deliver large-scale data systems and data platforms.
• Build batch and streaming data pipelines across cloud platforms.
• Mentor junior team members and contribute to delivery.
• Automate operations, observability, and telemetry pipelines.
• Provide project estimates and feasibility assessments.

Skills

End-to-end data pipelines

Public cloud platforms

Python proficiency

MLOps concepts

Cross-functional teamwork

Communication skills

Tools

AWS

Azure

Google Cloud Platform

Databricks

Snowflake

BigQuery

Redshift

Delta Lake

Spark

Glue ETL

Lambda

Kubernetes

Job description

Publicis Sapient in Chicago is seeking a Manager Big Data Engineering to lead design and delivery of scalable data platforms. You will steer cross-functional teams, translate client requirements into robust data solutions, and drive modernization across batch and streaming pipelines.

The role emphasizes strong cloud experience, Python and data modeling, with a focus on AI-enabled use cases, observability, and production operations.