Sr. Data Engineer

We are seeking a Senior Data Engineer with 4+ years of experience in building scalable, distributed, and high-performance data systems. In this role, you will architect, develop, and optimise real-time pipelines and analytical systems that enable Amazon teams to extract actionable insights and power intelligent decision-making across the organisation.
Responsibilities:
Design, build, and maintain real-time and batch data pipelines for structured and unstructured datasets.
Develop scalable data ingestion, transformation, and processing frameworks for high-volume data environments.
Collaborate with product, analytics, and infrastructure teams to ensure data reliability, availability, and performance.
Build APIs and data models that support large-scale analytics and machine learning applications.
Optimise query performance, storage systems, and ETL workflows for massive datasets.
Mentor junior engineers, contribute to best practices, and lead design reviews for critical data infrastructure.
Requirements:
4+ years of experience in data engineering, backend development, or large-scale data systems.
Strong proficiency in Python; experience with Java or Scala is a plus.
Hands-on experience with real-time processing frameworks such as Kafka, Spark Streaming, or Flink.
Solid understanding of data modelling, distributed systems, and API integrations.
Proficiency with SQL and NoSQL databases and working experience on AWS (S3 EMR, Redshift, Glue, Kinesis).
Familiarity with web scraping frameworks (Scrapy, Selenium, Playwright) or similar data acquisition tools.
Experience in optimising ETL pipelines and handling large-scale datasets.
Preferred Qualifications:
Experience in AI/ML data pipelines or analytical dashboarding.
Exposure to workflow orchestration tools (Airflow, Step Functions, or similar).
Experience mentoring engineers or leading small technical teams.

Experience
5-9 yrs