Senior Business Intelligence Engineer

4 days ago

Kottayam, Kerala, India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Job Title

Our company is a leading, global ad tech firm focusing on transparent and efficient paths for advertiser budgets to become publisher revenue.

The platform powers major global publishers and ad-tech businesses at scale across ad formats. Our proprietary contextual technology enhances programmatic buying, the latest industry standard in ad buying for digital platforms.

Role Overview

As a Data Applications Lead, you will be responsible for end-to-end delivery of data modules and platforms powering core business use cases. You will lead a small team of engineers and work closely with data science, analytics, and platform engineering teams.

You will need a strong foundation in SQL and databases, coupled with working experience on big data systems. This is a hands-on leadership role for someone who enjoys solving high-scale data challenges while mentoring others and driving execution.

Responsibilities

  • Develop and enhance data-heavy modules across ad serving, analytics, and reporting systems.
  • Design, optimize, and maintain scalable data pipelines using 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.
  • 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.

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