LEAD DATA ENGINEER (3847) | (BM113)

Prodigious


Company Description At Publicis Groupe, we are looking for a Data Engineer fluent in English to join Publicis Global Delivery, the outstanding platform that we created to become a global interconnected network and provide offshore & nearshore solutions for our partners - sister companies´ business worldwide. We are a never sleeps machine of creation that continuously grows and mutates to become a more efficient and collaborative system. A cross-media transformation agent, based in Argentina, Colombia, Costa Rica and Mexico, that provides centralized expertise of all Publicis Global Services' capabilities to enable consistent and standardized delivery across Media, Production, Commerce, Content, Data & Technology. **Job Description**: **What you’ll do**: **Responsibilities**: - Create and maintain optimal data pipeline architecture, including table design. - Assemble large, complex data sets that meet functional / non-functional business requirements. - Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. - Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and (GCP, AWS, Azure, Snowflake) ‘big data’ technologies. - Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics. - Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. - Create data tools for analytics and data scientist team members that assist them in building and optimizing advanced analytics and data models. - Work with data and analytics experts to strive for greater functionality in our data systems. **Qualifications**: **We’re looking for strong, impactful work experience, which typically includes**: - Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. - Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. - Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. - Build processes supporting data transformation, data structures, metadata, dependency, and workload management. - A successful history of manipulating, processing and extracting value from large disconnected datasets. - Strong project management and organizational skills. - Experience supporting and working with cross-functional teams in a dynamic environment. - Experience with relational SQL and NoSQL databases, including Postgres and Cassandra. - Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc. - Experience with big data tools: Hadoop, Spark, Kafka, etc. - Experience with AWS cloud services: EC2, EMR, RDS, Redshift, Athena - Experience with GCP cloud services: BigQuery, GCS, Cloud SQL, ML, Pub/Sub, DataProc - Experience with Azure cloud services: DataBricks, - Experience with stream-processing systems: Storm, Spark-Streaming, etc. - Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc. - Experience with data architecture creating staging and final table design. - Experience creating ERD / Data Dictionary documentation. Additional Information **Benefits**: - Access to Prepaid Medical Plan - Flexible schedule - 100% Remote work - 14 business days of vacation - English lessons - Discounts on courses, trainings and universities - Access to E-Learning platforms - Technical trainings & soft skills development - Certification programs - Level up program - Engagement activities and events - A mentor who´ll do a coaching process with you to develop your professional career!

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