Senior Associate Big Data Cloud Engineering Atlanta Hybrid

Publicis Sapient is a digital transformation partner helping established organizations get to their future digitally enabled state both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods fusing strategy consulting and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next our 20000 people in 53 offices around the world combine experience across technology data sciences consulting and customer obsession to accelerate our clients businesses through designing the products and services their customers truly value.

This is a hybrid role

Publicis Sapient is looking for a Senior Associate Data Engineer to be part of our team of top-notch technologists. You will lead and deliver technical solutions for large-scale digital transformation projects. Working with the latest data and AI engineering technologies in the industry you will be instrumental in helping our clients evolve for a more digital and AI-enabled future.

• Combine your technical expertise and problem-solving passion to work closely with clients turning complex ideas into end-to-end data solutions that transform our clients business.
• Translate client requirements into system design and develop solutions that deliver measurable business value.
• Lead design develop and deliver large-scale data systems data processing data transformation and data platform modernization initiatives.
• Build and optimize batch and streaming data pipelines across modern cloud data platforms and distributed processing frameworks.
• Support AI-enabled engineering use cases by designing high-quality data foundations retrieval patterns context engineering approaches and scalable data services that power agentic and machine learning solutions.
• Automate data platform operations and manage post-production systems observability quality reliability and operational processes including telemetry pipelines that capture prompt response trace latency token and cost data for AI-enabled services in a query able form.
• Conduct technical feasibility assessments and provide project estimates for the design and development of solutions.
• Mentor support and grow junior team members while contributing hands-on to delivery.

• Demonstrable experience implementing end-to-end data pipelines and production-grade data platforms.
• Hands-on experience with at least one leading public cloud data platform: Amazon Web Services Microsoft Azure or Google Cloud Platform;
• Experience with Databricks as a data engineering platform is strongly preferred including working with notebooks jobs Delta Lake or similar lakehouse patterns.
• Strong Python proficiency and practical experience using Python-based tooling for data engineering automation platform development or AI engineering workflows.
• Implementation experience with column-oriented database technologies such as BigQuery Redshift Vertica or similar platforms; NoSQL database technologies such as DynamoDB Bigtable Cosmos DB or similar; and traditional database systems such as SQL Server Oracle or MySQL.
• Experience implementing data pipelines for both streaming and batch integrations using tools and frameworks such as Glue ETL Lambda Google Cloud Dataflow Azure Data Factory Spark Spark Streaming or similar technologies.
• Experience with data modeling warehouse design fact/dimension implementations and modern lakehouse or data mesh patterns.
• Experience with code repositories continuous integration automated testing release management and production support practices.
• Familiarity with MLOps concepts and the data engineering responsibilities required to support AI/ML deployment validation monitoring rollback and operational reliability.
• Ability to handle module or track-level responsibilities while contributing to tasks hands-on.
• Good communication skills and willingness to work as part of a collaborative cross-functional team.

• Exposure to AI engineering patterns including context engineering retrieval-augmented generation support patterns agent architectures and production data services that support AI-enabled experiences.
• Experience building and maintaining the pipelines behind retrieval systems including document parsing chunking metadata extraction embedding generation and incremental reindexing alongside the vector databases graph databases semantic search and knowledge retrieval structures they feed.
• Exposure to agentic platforms or cloud AI services such as Vertex AI Azure AI services AWS AI services or comparable platforms; specific platform experience is less important than understanding how AI engineering differs from traditional data engineering.
• Practical experience deploying agents integrating agent frameworks or supporting agentic workflows in production or near-production environments is a plus.
• Experience building evaluation data infrastructure for AI systems including ground-truth and golden datasets offline evaluation pipelines and the data scaffolding behind LLM-as-judge and regression testing.
• Experience modeling and persisting agent state including session context conversation history and memory stores treating them as a durable storage and data modeling problem rather than an application detail.
• Support AI-enabled engineering use cases by designing high-quality data foundations retrieval patterns context engineering approaches and scalable data services that power agentic and machine learning solutions applying the same lineage provenance and data contract rigor to context and retrieval sources that you would to a production warehouse.
• Experience with agentic harnesses or orchestration tools such as Pi Hermes Agent or similar platforms is a plus but not required.
• Experience with Snowflake and zero-copy architecture patterns is a plus particularly for retail financial services energy or CPG-oriented use cases.

• Developer certifications for AWS Google Cloud Microsoft Azure Databricks Snowflake or related cloud/data platforms.
• Demonstrated experience applying AI engineering concepts in practical business environments rather than only academic or research settings.
• Hands-on experience supporting AI/ML and LLM lifecycle needs such as model deployment support monitoring validation shadow deployments release management and evaluation or data quality measurement for both predictive models and generative systems.
• Experience in retail financial services energy CPG logistics manufacturing or other data-rich industries where applied AI and large-scale data engineering are used to solve operational or client-facing problems.
• Understanding of Agile product and delivery methodologies in consulting or client-facing environments.

Salary Range: $107000 - $130000

The range shown represents a grouping of relevant ranges currently in use at Publicis Sapient. Actual range for this position may differ depending on location and specific skillset required for the work itself.

• Flexible vacation policy; time is not limited allocated or accrued.
• 15 paid holidays throughout the year.
• Generous parental leave and new parent transition program.
• Tuition reimbursement.
• Corporate gift matching program.
• An inclusive workplace that promotes diversity and collaboration.
• Access to ongoing learning and development opportunities.
• Competitive compensation and benefits package.
• Flexibility to support work-life balance.
• Comprehensive health benefits for you and your family.
• Generous paid leave and holidays.
• Wellness program and employee assistance.

As part of our dedication to an inclusive and diverse workforce Publicis Sapient is committed to Equal Employment Opportunity without regard for race color national origin ethnicity gender protected veteran status disability sexual orientation gender identity or religion. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability you may contact us at