Hands-On Big Data Architect — Hybrid (Chicago)

Sapient Corporation; Arlington (VA); Hybride; USD 135 000 - 190 000; Plein temps

Avantages offerts par ce poste

Health benefits

Learning & development opportunities

Flexible work arrangements

Competitive compensation

Résumé du poste

Publicis Sapient is seeking a Manager of Big Data Engineering to design, build, and optimize data platforms that scale for high-performance analytics. The role is hybrid with Chicago as a focal location and requires leadership of cross-functional teams to deliver end-to-end data solutions.

The successful candidate will drive architecture, implement batch and streaming pipelines, and mentor junior engineers while collaborating with clients to translate requirements into measurable business value.

Qualifications

• Strong Python proficiency and practical experience using Python-based tooling for data engineering, automation, platform development, or AI engineering workflows.
• Experience implementing end-to-end data pipelines and production-grade data platforms.
• Hands-on experience with at least one leading public cloud data platform (AWS/Azure/GCP).
• Experience with Databricks as a data engineering platform, including notebooks, jobs, and Delta Lake.

Responsabilités

• Design, build, and optimize data platforms enabling scalable data processing and analytics.
• Lead large-scale data systems, data processing, and data platform modernization initiatives.
• Build and optimize batch and streaming data pipelines across cloud data platforms and distributed frameworks.
• Mentor junior team members and contribute hands-on to delivery.

Connaissances

Python proficiency

Data pipelines

Cloud data platforms

Outils

Databricks

AWS

Azure

GCP

BigQuery/Redshift

SQL/NoSQL databases

Description du poste

Publicis Sapient is seeking a Manager of Big Data Engineering to design, build, and optimize data platforms that scale for high-performance analytics. The role is hybrid with Chicago as a focal location and requires leadership of cross-functional teams to deliver end-to-end data solutions.

The successful candidate will drive architecture, implement batch and streaming pipelines, and mentor junior engineers while collaborating with clients to translate requirements into measurable business value.