
Chief Data Engineer
2 weeks ago
About Our Company:
We are a leading global ad tech company that focuses on creating the most transparent and efficient path for advertiser budgets to become publisher revenue.
Our proprietary contextual technology is at the forefront of enhancing programmatic buying, the latest industry standard in ad buying for digital platforms.
The Media.net platform powers major global publishers and ad-tech businesses at scale across ad formats like display, video, mobile, native, as well as search.
Our U.S. HQ is based in New York, and our Global HQ is in Dubai.
We take pride in the value-add we offer to our 50+ demand and 21K+ publisher partners, in terms of both products and services.
Role Overview
As a Data Applications Lead, you'll own end-to-end delivery of data modules and platforms that power core business use cases across real-time bidding, reporting, and analytics.
You will lead a small team of engineers and work closely with data science, analytics, and platform engineering teams.
Key Responsibilities:
- Lead the development and enhancement of data-heavy modules across ad serving, analytics, and reporting systems.
- Design, optimize, and maintain scalable data pipelines using a mix of SQL, NoSQL, and Big Data tools.
- Work with streaming platforms like Apache Kafka and Flink for real-time data processing.
- Ensure data reliability, low-latency access, and robustness across internal and external-facing systems.
- Collaborate with product managers, analysts, and other engineering teams to translate business needs into data solutions.
- Drive code reviews, mentor junior engineers, and contribute to architectural discussions.
Requirements:
- 5-8 years of experience working in data engineering or backend roles with a strong data focus.
- Solid command over SQL and RDBMS concepts – query optimization, indexing, schema design.
- Hands-on experience with Big Data and NoSQL technologies – Hive, Spark, Presto, HDFS, Kafka, MongoDB, Cassandra, etc.
- Strong programming skills in Python, Java, or Scala.
- Experience with large-scale data processing, batch & stream pipelines, and performance tuning.
- Exposure to distributed systems or cloud-based data platforms (AWS, GCP, or Azure) is a plus.
- Ability to take ownership and drive outcomes while mentoring and growing a small team.
Benefits:
- Work on internet-scale data systems – billions of rows processed on a regular basis.
- Solve high-impact problems at the intersection of advertising, machine learning, and data platforms.
- Be part of a high-calibre team with ownership and autonomy from day one.
- A tech-first culture that encourages learning, experimentation, and innovation.
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