Senior Associate Data Engineer - AI & Data Platforms

Publicis Groupe Holdings B.V; Bogotá; Presencial; COP 120.000.000 - 180.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Inclusive workplace

Learning opportunities

Competitive compensation and benefits

Flexible work arrangements

Descripción de la vacante

Publicis Sapient seeks a Senior Data Engineer to design, build, and modernize enterprise-scale data platforms across cloud environments. You will work across ingestion, lakehouse architectures, orchestration, governance, APIs, and modernization initiatives to transform fragmented data ecosystems into scalable, cloud-native solutions.

The role blends hands-on software engineering with technical design leadership, contributing to implementation while owning critical architectural decisions and

Formación

• 6+ years of experience in Data Engineering or related roles.
• Advanced Python and SQL development in enterprise environments.
• Strong hands-on Spark/PySpark experience for large-scale processing.
• Deep expertise in AWS or Azure and familiarity with a second cloud.
• Solid data modeling skills (Star/Snowflake/SCD2).
• Experience building CI/CD pipelines and data deployment practices.
• Proven ability to design, build, and deploy data services and APIs.
• Experience with AI/LLM-enabled data solutions is a plus.
• Ability to defend technical designs and balance design with delivery ownership.

Responsabilidades

• Design and deliver enterprise data platforms end-to-end, from ingestion through production-ready services.
• Build ingestion, replication, and transformation frameworks across source systems.
• Implement scalable lakehouse architectures supporting analytics and downstream apps.
• Model dimensional/historical data for auditability and regulatory needs.
• Analyze legacy systems and contribute to target-state architectures and governance.
• Develop APIs and reusable data services that expose curated data products.
• Architect AI-enabled data services with LLMs, embeddings, and vector databases.
• Lead technical design discussions and influence cross-functional teams.

Conocimientos

Python

SQL

Spark/PySpark

AWS/Azure

Data Modeling

CI/CD

API/Data Services

AI/LLM Data Solutions

Architecture Design

Stakeholder Communication

Descripción del empleo

Overview

We're seeking a Senior Data Engineer to design, build, and modernize enterprise-scale data platforms across cloud environments. You will work across data ingestion, lakehouse architectures, orchestration, governance, APIs, and modernization initiatives, helping clients transform fragmented and legacy data ecosystems into scalable, cloud-native platforms.

This role combines hands‑on software and data engineering with technical design leadership. Work is hands‑on and design‑oriented in equal measure, requiring you to contribute directly to implementation while also owning critical technical decisions, architecture designs, and engineering standards. As enterprise platforms increasingly enable intelligent products and services, you will also build data services and platform capabilities that incorporate AI and LLM‑based solutions where they provide measurable business value.

Responsibilities

Your Impact

• Design and deliver enterprise data platforms end‑to‑end, from ingestion and modeling through orchestration, governance, and production‑ready services.
• Build ingestion, replication, and transformation frameworks across distributed and heterogeneous source systems.
• Implement scalable lakehouse architectures, including raw, conformed, and curated layers that support analytics, operational reporting, and downstream applications.
• Design dimensional and historical data models, including temporal modeling patterns that support auditability, traceability, and regulatory requirements.
• Analyze legacy systems, document dependencies, and contribute to target‑state architectures, migration sequencing, governance models, and integration contracts.
• Develop APIs and reusable data services that expose curated data products to applications, users, and AI‑powered systems.
• Design and operationalize AI‑enabled data services using LLM APIs, embeddings, retrieval architectures, vector databases, and model‑driven workflows.
• Evaluate AI and LLM solutions pragmatically, balancing accuracy, explainability, operational complexity, and business value.
• Establish engineering excellence through CI/CD automation, testing strategies, observability, lineage, metadata management, and technical documentation.
• Lead technical design discussions, evaluate architectural trade‑offs, and influence engineering decisions across multidisciplinary teams.

Qualifications

Skills & Experience

• 6+ years of experience in Data Engineering, Data Platform Engineering, or related fields with ownership of production systems.
• Advanced Python and SQL development experience in enterprise environments.
• Strong hands‑on experience with Spark or PySpark for large-scale distributed data processing.
• Deep expertise in AWS or Azure and practical experience working within a second cloud ecosystem.
• Strong data modeling capabilities including Star Schema, Snowflake Schema, Slowly Changing Dimensions (SCD Type 2), Medallion Architecture, and Lakehouse patterns.
• Experience designing and implementing CI/CD pipelines, automated testing, and deployment practices for data platforms and services.
• Strong relational database engineering and schema design experience.
• Experience building production‑grade data services, APIs, or backend components.
• Proven experience designing, integrating, or operating AI and LLM‑enabled solutions in enterprise environments.
• Proven ability to author, communicate, and defend technical designs with engineering stakeholders.
• Demonstrated ability to balance solution design responsibilities with hands‑on implementation and delivery ownership.

Set Yourself Apart With

• Experience building AI‑enabled data products using LLM APIs, Retrieval‑Augmented Generation (RAG), embeddings, semantic search, or vector databases.
• Experience developing backend services and APIs using FastAPI or similar frameworks.
• Experience working with regulated data domains requiring compliance, privacy, governance, and auditability controls.
• Familiarity with metadata management, cataloging, lineage, and enterprise data governance tooling.
• Experience supporting large‑scale cloud modernization and migration initiatives.
• Experience operating and delivering solutions across both AWS and Azure environments.
• Knowledge of MLOps, model evaluation frameworks, and AI observability practices.

Additional information

• 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 [e-mail]