
Senior Data Engineer @ RTB House
19 hours ago
- 5+ years of hands-on experience in data engineering roles, building and maintaining large-scale distributed data systems.
- Proven experience working with petabyte-scale datasets and high-throughput systems.
- Strong programming skills in Python, Java, or Scala.
- Solid understanding of database management systems (both relational and non-relational).
- Expertise with big data frameworks such as Hadoop, Spark, or Flink.
- Familiarity with databases such as MySQL, PostgreSQL, MongoDB, or Cassandra.
- Knowledge of cloud platforms and their Big Data solutions (e.g., GCP BigQuery).
- Excellent analytical and problem-solving abilities.
- Clear communication skills with the ability to work cross-functionally.
- A passion for continuous learning and staying current with the latest developments in data engineering.
We Are:
RTB House is a global company that provides state-of-the-art marketing technologies for top brands and agencies worldwide. Its proprietary ad-buying engine is the first in the world to be powered entirely by Deep Learning algorithms, enabling advertisers to generate outstanding results and reach their goals at every stage of the funnel.
Why RTB House?
We are a data-driven company where technology positions us as a leader in programmatic advertising. We work with thousands of clients across EMEA, APAC, and the Americas. Our highly optimized system serves over 20M QPS, generating petabytes of various data points.
We are looking for a skilled Senior Data Engineer with extensive and diverse experience — ideally gained across several companies that process data at large scale — to join our team.
You will:
Data Architecture & Infrastructure
- Design and implement data structures that support large volumes of data and meet organizational needs.
- Establish data quality standards and guidelines, define validation rules, and implement automated monitoring processes to detect and correct data anomalies.
- Design and maintain data infrastructure that ensures timely and accurate data flow across the organization.
- Work with various technologies, including databases, data warehouses, and data lakes.
- Optimize the infrastructure for cost, performance, scalability, and reliability.
- Consider factors such as data volume, velocity, and variety when building and maintaining data infrastructure.
- Proactively monitor and troubleshoot the data infrastructure to ensure smooth operation and resolve any issues.
Collaboration & Communication:
- Work closely with data scientists, analysts, and other stakeholders to understand their requirements and translate them into scalable, efficient data solutions.
- Use clear and concise communication to explain technical concepts, discuss project requirements, and present findings and recommendations.
- Support and mentor junior engineers when needed, fostering best practices in data engineering.
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