Senior Data Engineer

About the role

Our client is looking for an experienced Senior Data Engineer to design and deliver cloud‑native data platforms on AWS and Microsoft Azure. You will work closely with data scientists, engineering teams and business stakeholders to build scalable, secure and AI‑ready data ecosystems.

Key responsibilities

• Architect and implement end‑to‑end ETL/ELT pipelines and cloud‑native data platforms.
• Lead AWS solutions using S3, Glue, EMR, Lambda, Kinesis and Athena.
• Design Azure integration using Data Factory, Synapse Analytics, Databricks and Event Hub.
• Build resilient streaming platforms with Apache Kafka, Amazon Kinesis and Azure Event Hub.
• Develop Kafka consumer applications using Kafka Streams, Spark Structured Streaming and Apache Flink.
• Manage Kafka consumer groups, offset handling, schema evolution and monitoring.
• Create AI‑ready data platforms, feature stores and automated model deployment pipelines.
• Establish data quality, metadata management, governance and lineage frameworks.
• Optimize pipelines for performance, scalability, cost efficiency and high availability.
• Implement Infrastructure‑as‑Code and CI/CD pipelines with Terraform and CloudFormation.
• Mentor junior engineers and provide technical leadership.

Required profile

• Strong analytical and problem‑solving abilities.
• Excellent communication and stakeholder engagement skills.
• Proven ability to architect enterprise‑scale cloud data platforms.
• Leadership and mentoring experience.
• Attention to detail with focus on quality and operational excellence.
• Ability to manage multiple priorities in complex environments.

Required skills

• Amazon S3
• AWS Glue
• Amazon EMR
• AWS Lambda
• Amazon Kinesis
• Amazon Athena
• Azure Data Factory
• Azure Synapse Analytics
• Azure Databricks
• Azure Event Hub
• Apache Kafka
• Kafka Streams
• Spark Structured Streaming
• Apache Flink
• Terraform
• AWS CloudFormation
• CI/CD pipeline implementation