Senior Data Engineering Architect - Lead Scalable Platforms

Publicis Sapient; Arlington (VA); Hybrid; USD 160,000 - 262,000; Full time

Benefits offered by this job

Competitive compensation

Flexible leave & balance

Wellness program

Job summary

Publicis Sapient is seeking a Senior Manager Data Engineering (Technology Architect) to design and implement scalable data platforms that enable data-driven decision-making. You will lead end-to-end data solutions, architect large-scale data systems, and mentor junior engineers across batch and streaming pipelines on cloud platforms.

You will work with clients to translate requirements into system designs, drive data platform modernization, and ensure high-quality data foundations for AI-enabled

Qualifications

• Hands-on experience delivering end-to-end data pipelines and production-grade platforms.
• Experience with at least one major cloud data platform (AWS, Azure, or GCP).
• Preferred Databricks experience with notebooks, jobs, Delta Lake, or lakehouse patterns.
• Strong Python and data engineering tooling skills.
• Exposure to MLOps concepts and AI/ML lifecycle support.

Responsibilities

• Design and implement scalable data platforms and pipelines for data-driven decisions.
• Lead data architecture and modernization initiatives across batch and streaming workloads.
• Build and optimize data pipelines on cloud platforms and distributed frameworks.
• Support AI-enabled engineering use cases with robust data foundations and retrieval patterns.
• Mentor junior team members and contribute hands-on to delivery.

Skills

Python

Cloud data platforms

Databricks

Data pipelines

MLOps

Communication

Tools

Snowflake

BigQuery/Redshift

DynamoDB/Cosmos DB

Job description

Publicis Sapient is seeking a Senior Manager Data Engineering (Technology Architect) to design and implement scalable data platforms that enable data-driven decision-making. You will lead end-to-end data solutions, architect large-scale data systems, and mentor junior engineers across batch and streaming pipelines on cloud platforms.

You will work with clients to translate requirements into system designs, drive data platform modernization, and ensure high-quality data foundations for AI-enabled