Design and implement data ingestion and processing from diverse sources, leveraging 'big data' technologies, including related AWS services: Spark, Glue, Airflow, Kafka, Data Pipeline, NoSQL DBs, SageMaker, and ML Studio.
Develop and maintain data tools for data science and analyst teams, supporting AI/ML model building, optimization, and productionization.
Assemble large, complex data sets for a data lakehouse, emphasizing advanced data modeling techniques including star schemas.
Create data pipelines for actionable insights in areas like marketing automation, customer acquisition, and other key business domains.
Guide and support fellow data engineers, assuming a leadership position in assigning and ensuring the successful completion of data engineering tasks within a diverse and collaborative product team.
Collaborate with stakeholders to address data-related technical issues, support data infrastructure needs, and optimize data delivery and scalability within the AWS environment.
Support pre-sales activities by proposing technical solutions, providing accurate effort estimates, and showcasing expertise in AWS Cloud Technologies.
Proven experience building and productionizing big data architectures, pipelines, and datasets within AWS.
Solid understanding of AWS 'big data' concepts and patterns, including data lake, lambda architecture, streaming processing, DWH, BI, and reporting.
Deep hands-on development experience in the AWS environment, with a focus on AWS services like Glue, EC2, EMR, RDS, Redshift, Sagemaker, etc.
4+ years of experience in a Data Engineer role, demonstrating expertise in big data tools (Spark, Kafka), object-oriented/scripting languages (Python, Scala, Java, R, C++), and AWS cloud services.
Implementation of large-scale data-oriented pipelines/workflows using ETL tools and extensive experience with relational (like MS SQL, PostgreSQL, Redshift) and NoSQL databases (Cassandra, MongoDB, Dynamo DB).
Proficiency in data modeling techniques, including dimensional modelling and star schemas.
Relevant analytic skills related to structured and unstructured datasets.
Ample experience in utilizing CI/CD automation tools
Good project management and organizational skills.
Preferred Skills:
Past experience delivering business intelligence projects using tools like PowerBI, Tableau, Qlick Sense, Keboola.
Working knowledge of message queuing, stream processing, and highly scalable real-time data processing using technologies like Kafka.
Experience with data pipeline/workflow management tools such as Airflow, Kestra, AWS Glue.
With us, you will become part of:
We, obviously, offer even more:
⛺ 5 weeks of vacation + 3 wellness days
❤️ 2 Volunteering days to share the kindness of your heart with others
⏰ Flexible working hours and home office
🎯 Fully covered certifications in AWS, Adobe, Microsoft, Snowflake etc.
🎓 Full access to Dentsu Academy, on-site learning sessions
🐶 Pet friendly offices
💌 Edenred meal and cafeteria points
🍹 Team events: company parties, monthly breakfasts, and pub quizzes
🥪 Snacks, and drinks at the office
💸 Referral bonus programme
💻 Laptop + equipment
📞 Corporate mobile phone subscription
