Data Engineer

The dentsu group is a global marketing communication network that responds to the needs of the digital age with its offer. It includes the following brands: Carat, Isobar, iProspect, Red8 Advertisement, Amplifi, DDS, dentsu and dentsu X. The dentsu group operates in 110 countries around the world, employing over 45,000 experts. In Poland, it has been operating in its current form since 2005 and employs about 700 people serving over 200 clients. 

dentsu strives to be the network of choice worldwide for customers looking for expertise and the greatest capacity in brand, media and digital communications services. 

Due to dynamic development, we are looking for a person for the position of Data Engineer. 

We are seeking a passionate and skilled Data Engineer to join our data engineering team. The primary responsibilities of this role will focus on ETL processes, cloud administration, and data warehouse maintenance within our Google Cloud ecosystem. 

Key Responsibilities:  

• Architect, build, and sustain scalable ETL workflows utilizing Apache Airflow within the Google Cloud Composer environment. 

• Write high-quality, readable, and maintainable code, following best practices and PEP8 guidelines. 

• Create, modify, and maintain DAGs. 

• Develop custom hooks and connectors for interacting with various services, such as APIs, databases, and FTP servers. 

• Work with CI/CD pipelines and containerization technologies like Docker. 

• Contribute to the upkeep and advancement of our BigQuery data warehouse infrastructure. 

• Handle data modeling, schema creation, and maintenance of datasets. 

• Optimize and operationalize queries. 

• Oversee, administer, and fine-tune Google Cloud Platform resources. 

• Provision assets and maintain current architecture. 

• Manage access control (IAM). 

• Assist in the creation and enhancement of internal applications aimed at automating key business processes. 

• Assist with the development of FastAPI-based APIs. 

• Implement and maintain Cloud Run and Cloud Functions backend microservices. 

• Assist in deploying ML solutions in collaboration with the Data Science Team 

• Provide and optimize large datasets tailored for Data Science initiatives 

• Optimize data transformations by fine-tuning SQL queries and data pipelines to enhance performance and reduce computational costs. 

• Manage the deployment of ML models into production environments. 

Skills and Qualifications: 

Must-Have: 

• Python:  

• Proficiency in Python programming, with experience in libraries commonly used in data engineering. 

• Object-Oriented Programming (OOP): Experience with OOP principles and design patterns. 

• Coding Best Practices: Experience with writing idiomatic and maintainable code, adhering to PEP8 guidelines. 

• SQL:  

• Skilled in SQL, including both Data Definition Language (DDL) and Data Manipulation Language (DML). 

• Version Control:  

• Familiarity with version control systems, preferably Git. 

• Linux Environment:  

• Comfortable working in Linux-based systems, utilizing the Windows Subsystem for Linux (WSL) where necessary. 

• Console: Competency in using command-line interfaces. 

Nice-to-Have: 

• Apache Airflow:  

• Experience with orchestration using Apache Airflow. 

• Cloud Platforms:  

• Familiarity with Google Cloud Platform or other cloud service providers. 

• BigQuery:  

• Hands-on experience with BigQuery for data warehousing solutions. 

• Docker:  

• Basic knowledge of containerization technologies, primarily Docker. 

• DBT (Data Build Tool):  

• Experience with DBT for analytics engineering and transformation. 

Bonus Points: 

• Industry Experience:  

• Past experience in the marketing industry is highly desirable. 

• Marketing Tools:  

• Familiarity with online marketing tools such as Google Marketing Platform, Google Analytics.