Data Engineering Associate Director
Summary
Senior data engineering lead at Publicis Global Delivery who owns partner data integrations, builds and maintains ETL pipelines, harmonizes cross-channel data, and enforces data quality, governance, and automation. Core stack is Python, SQL/BigQuery, and Databricks/Spark, with Tableau and Alteryx as pluses.
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.