Data Engineering Associate Director
Publicis Groupe · Bogotá
Company descriptionPublicis 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. |
| 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. |
| 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 |
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