Data Engineering Associate Director

Publicis Groupe; Bogotá ciudad; Híbrido; COP 120.000.000 - 190.000.000; Jornada completa

Descripción de la vacante

Publicis Global Delivery (PGD) in Bogotá is seeking a senior data engineer to lead data integration, ETL design, and scalable data architecture for partner data. You will collaborate with analytics and account teams to drive reliable data flows and dashboards.

The role requires 10+ years of data engineering experience, advanced Python, BigQuery, and Spark expertise, and a proven ability to implement enterprise-grade data solutions.

Formación

• Education: Bachelor’s Degree in Computer Science, Mathematics, or a related engineering field.
• Experience: 10+ years in data engineering with large-scale data processing.

Responsabilidades

• Own and manage partner data relationships to ensure seamless data integration.
• Develop and maintain the infrastructure required for ETL of data from diverse sources.
• Ensure continuous synchronization of data across platforms and partners.
• Fully own data harmonization across cross-channel data streams.
• Develop and enforce data quality and governance best practices.

Conocimientos

Python

BigQuery

Databricks/Spark

Data integration

Data pipelines

Enterprise data architecture

Educación

Bachelor’s Degree in Computer Science, Mathematics, or related engineering field

Herramientas

Databricks/Spark

BigQuery

Alteryx

Tableau

Descripción del empleo

Company description

Publicis Global Delivery (PGD); Publicis Groupe’s industry leading globally connected capability platform. Where talent, technology & operations combine to delivery amazing solutions for our clients. Expertise across Media, Data, Technology, Commerce & Production in all regions of the world.

PGD is comprised of the best talent, and ways-of-working, which enables global scale, innovation and transformation, each day.

Culture, growth and wellbeing underline all aspects of Publicis Global Delivery.

#WeArePGD

Responsibilities

Innovation and Evaluation

• Stay informed on emerging data technologies and tools.
• Regularly evaluate existing tools and procedures and propose improvements where applicable.

Risk Management and Compliance

• Identify and mitigate risks associated with data integration and processing.
• Ensure data processing practices comply with industry standards and regulations.

Data Integration and Management

• Own and manage all partner data relationships to ensure seamless data integration.
• Develop and maintain the infrastructure required for optimal extraction, transformation, and loading (ETL) of data from a wide variety of data sources.
• Ensure continuous synchronization of data across platforms and partners.

Cross-Channel Data Harmonization

• Fully own the harmonization process of cross-channel data, creating a unified data stream.
• Implement processes for regular updating and validation of cross-channel data consistency.

Quality Assurance (QA) and Best Practices

• Develop and enforce best practices for data quality assurance and data governance.
• Implement automated systems for data quality checks and error notifications.

Automation and Optimization

• Automate repetitive data processing tasks to improve efficiency and accuracy.
• Continuously optimize data workflows to ensure high performance and reduced latency.

Documentation and Reporting

• Maintain comprehensive documentation for all data processes, pipelines, and integrations.
• Ensure transparency of processes and facilitate knowledge sharing within the team.

Collaboration and Training

• Work closely with analytics and account teams to understand data needs and priorities.
• Provide training and support for staff on using dashboards and understanding data flows.

Qualifications

Required Skills and Experience:

• Education: Bachelor’s Degree in Computer Science, Mathematics, or a related engineering field.
• Experience: 10+ years of experience in data engineering roles with a focus on large-scale data processing.

Technical Proficiency (Required):

• Advanced Python skills for data manipulation and pipeline development.
• Strong expertise in relational SQL databases, particularly BigQuery.
• Hands-on experience with Databricks or Spark for big data processing.
• Experience with integration of data from diverse sources.
• Experienced in design, implementation and support/evolution of enterprise grate Data centric solutions.
• Experience in Scalable, Secure, Enterprise Grade data architecture solutions definition

Additional information

Desirable:

• Knowledge of ETL tools such as Alteryx.
• Experience with data visualization tools like Tableau to support client-facing insights.