Principal AWS Data Engineer

Design and build end-to-end data pipelines leveraging AWS-native tools and modern data architectures.

Collaborate with clients to gather requirements, define solutions, and deliver production-grade systems.

Apply AWS Well-Architected Principles to ensure scalability, security, and resilience.

Lead in the development of robust, tested, and fault-tolerant data engineering solutions.

Support and mentor junior engineers, contributing to knowledge sharing across the team.

Proficient in one of Python, Scala or Java, with strong experience in Big Data technologies such as: Spark, Hadoop etc.

Practical knowledge of building real-time event streaming pipelines (e.g., Kafka, Spark Streaming, Kinesis).

Expertise in Data Modelling, schema design, and handling both structured and semi-structured data.

Familiarity with distributed systems such as Hadoop, Spark, HDFS, Hive, Databricks.

Exposure to AWS Lake Formation and automation of ingestion and transformation layers.

Background in delivering solutions for highly regulated industries.

Passion for mentoring and enabling data engineering best practices across teams.