Analytics Engineer (Contract)

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

Job Description

As an Analytics Engineer, you will design, build, and maintain scalable data pipelines and solutions that transform data from complex marketing and enterprise systems into reliable, well-structured datasets. You will work across APIs, cloud data platforms, and sources such as Salesforce to ensure data is accurately ingested, integrated, modelled, documented, and made available for downstream analytics, reporting, and advanced modelling. You will also leverage modern AI tools to enhance engineering workflows and help build well-documented, AI-ready data assets that support evolving business and technology needs.

Job Description

As an Analytics Engineer, you will design, build, and maintain scalable data pipelines and solutions that transform data from complex marketing and enterprise systems into reliable, well-structured datasets. You will work across APIs, cloud data platforms, and sources such as Salesforce to ensure data is accurately ingested, integrated, modelled, documented, and made available for downstream analytics, reporting, and advanced modelling. You will also leverage modern AI tools to enhance engineering workflows and help build well-documented, AI-ready data assets that support evolving business and technology needs.

Your Impact:

• Design, build, and maintain scalable, reliable data pipelines that ingest and integrate data from marketing platforms, Salesforce, APIs, and other enterprise data sources.
• Develop data transformations and models that provide trusted, well-structured datasets for downstream analytics, reporting, dashboarding, and advanced modelling.
• Build and maintain API-based integrations and custom Python solutions to support reliable and automated data ingestion.
• Ensure data quality, integrity, and availability through validation, testing, monitoring, and troubleshooting of data pipelines and integrations.
• Create and maintain technical documentation, metadata, data definitions, and lineage to improve the discoverability, usability, and governance of data assets.
• Build and structure datasets and documentation to support AI and LLM use cases, while leveraging AI tools throughout development, testing, troubleshooting, and documentation workflows.

Your Skills & Experience

• 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.
• Hands