Data Platform Engineer

We are looking for a strong, hands-on Data Platform Engineer to join our team and play a key role in building our data infrastructure from the ground up.

In this role, you will design and implement scalable data pipelines and platforms, supporting both batch and real-time use cases.

You will work closely with analysts and stakeholders to deliver reliable, high-quality data solutions, and take full ownership of data flows - from ingestion to consumption.

This is a great opportunity for an executor who enjoys building, moving fast, and making an impact.

What will your job look like?

• Design, build, and maintain the underlying infrastructure for a modern cloud-based data platform.
• Implement and manage CI/CD processes for data pipelines and platform deployments across development and production environments.
• Design and manage secure, scalable AWS-based data infrastructure, including IAM roles, permissions, policies, networking, and environment isolation.
• Build and maintain orchestration, monitoring, alerting, and observability capabilities for data pipelines and platform services.
• Support deployment, reliability, and operational excellence of data workloads running on technologies such as Spark, DBT, Airflow, Athena, and AWS services.
• Collaborate closely with Data Engineers, Analysts, BI teams, and IT/Cyber teams to ensure secure and scalable data operations.
• Monitor, troubleshoot, and optimize platform performance, availability, and cost efficiency.
• Establish best practices for infrastructure-as-code, deployment standards, security, and production readiness.

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• 5+ years of hands-on experience in Data Engineering, Platform Engineering, DevOps, or Cloud Infrastructure roles.
• Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
• Strong hands-on experience with AWS , including services such as IAM, S3, Athena, CloudWatch, networking, permissions, and security policies.
• Experience managing development and production environments, deployment processes, and CI/CD pipelines.
• Experience supporting and operating data platforms and pipelines in production environments.
• Strong understanding of data engineering concepts and modern data architectures (batch and real-time).
• Experience working with Spark, Airflow, and cloud-based data processing frameworks .
• Strong Python and SQL skills.
• Experience with monitoring, logging, alerting, and operational troubleshooting of data systems.
• Experience with Infrastructure as Code tools (Terraform / CloudFormation) - Advantage
• Experience with Kubernetes, containerized environments - Advantage
• Experience with Kafka, Iceberg, Databricks, Snowflake - Advantage
• Strong ownership and execution mindset, with the ability to work in fast-paced and ambiguous environments.
• Fluent in English.