Staff Engineer - Data Engineer
Portugal, Lisboa, LisbonEngineering
The Data Engineering team at Smaato works on a few very interesting technology problems
related to big data, distributed computing, low latency, analytics, visualization, machine
learning, and highly scalable platform development. We build reliable, peta bytes scale
distributed systems using technologies such as Spark, Hadoop, Apache Flink, Airflow, Kafka, and
Druid. As part of Smaato, you will work on the applications where all threads come together:
Streaming, Processing, and Storage of the Ad exchange. Our ultra-efficient exchange processes more
than 125 billion ad requests daily, e.g. whopping 3.5 trillion in a month. Every line of code you
write matters as it is likely to be executed several billion times a day. We are one of the biggest
AWS users with a presence in four different regions.
Smaato’s data platform is a symphony of streams, orchestrations, microservices, schedulers,
analytics, and visualization technologies. The platform is supported by polyglot persistence using
Druid, DynamoDB, Vertica, MySQL, and a bunch of orchestration & streaming frameworks like
Airflow, Spark, Flink.
The job will involve constant feature development, performance tuning, and platform stability
assurance. The mission of our analytics team is “data-driven decisions at your fingertips”. You
own and provide the system on which all business decisions will be based. Precision and high-
quality results are essential in this role.
Our engineers are passionate problem solvers. Be it Java, Python, Scala, Groovy, or
typescript, we are up for all games .
What You’ll Do
Design and architect data platform components supporting millions of requests per
This role is 70% hands-on, enhancing and supporting data pipeline components.
Lead small team, coordinate with the product team, lead automation, and review code.
Delivering high-quality software, meeting timelines, and being agile.
Maintain the current platform and shape its evolution by adopting new technologies.
Closely collaborate with stakeholders to gather requirements and design new product
features in a short feedback loop
12+ years of experience in Big-data platforms, or distributed systems, with a deep
understanding of Apache Druid, AWS, Spark, and Airflow.
Exposure to highly scalable, low latency microservices development.
Strong exposure to application, enterprise, and microservice design patterns.
Strong understanding of computer science fundamentals, algorithms, and data
Proficient in one or more programming languages – java, python, scala.
Exposure to AWS, Automation, and DevOps (Kubernetes, Jenkins CICD pipelines).
Experience in leading a small team of highly productive engineers.
Proven experience in owning the products and driving their end-to-end, all the way
from gathering requirements, development, testing, and deployment to ensuring high
Contribute to architectural and coding standards, evolving engineering best practices.
Nice to have - Open-source committer/contributor / PMC in any of these Apache big
data open-source technologies
You enjoy operating your applications in production and strive to make on-calls
obsolete, debugging issues in their live/production/test clusters, and implementing
solutions to restore service with minimal disruption to the business. Perform root cause
The team is looking for passionate engineers, ready to embrace technology to deliver next-generation data