AI-Driven Analytics Engineer: Scalable Data Pipelines

Publicis Sapient; Atlanta (GA); On-site; USD 120,000 - 160,000; Full time

Job summary

Publicis Sapient is seeking an Analytics Engineer to design, build, and maintain scalable data pipelines that transform data from Salesforce, APIs, and marketing platforms into reliable datasets for analytics and AI use cases. You will work across cloud platforms to ensure accurate ingestion, modeling, and documentation.

The role emphasizes strong SQL/Python skills, production-grade data pipelines, and data governance, with opportunities to leverage AI tools to enhance engineering workflows and

Qualifications

• 5+ years of experience in analytics engineering or a similar data-focused engineering role.
• Strong SQL and Python skills, with experience building and maintaining production-grade data pipelines.
• Experience integrating data from marketing platforms, CRM systems, and APIs.
• Ability to design, document, and govern data assets for analytics, reporting, and AI use cases.

Responsibilities

• Design, build, and maintain scalable data pipelines across marketing platforms, Salesforce, APIs, and enterprise sources.
• Develop data transformations and models for trusted, well-structured datasets for analytics, reporting, dashboards, and modeling.
• Build and maintain API-based integrations and Python solutions for reliable automated data ingestion.
• Ensure data quality, integrity, and availability through validation, testing, monitoring, and troubleshooting.
• Create and maintain technical documentation, metadata, definitions, and data lineage.
• Structure datasets and documentation to support AI and LLM use cases with AI-ready data assets.

Skills

SQL

Python

Data pipelines

Tools

Salesforce

API integrations

Job description

Publicis Sapient is seeking an Analytics Engineer to design, build, and maintain scalable data pipelines that transform data from Salesforce, APIs, and marketing platforms into reliable datasets for analytics and AI use cases. You will work across cloud platforms to ensure accurate ingestion, modeling, and documentation.

The role emphasizes strong SQL/Python skills, production-grade data pipelines, and data governance, with opportunities to leverage AI tools to enhance engineering workflows and