Job Title: Cloud Data Platform Engineer

Job Description

We are seeking an experienced Cloud Data Platform Engineer to support large-scale data engineering, data integration, and cloud platform initiatives for our financial services client, Mizuho. The ideal candidate will have a strong background in cloud-native data solutions, data pipelines, and enterprise data platforms, with hands-on expertise in building scalable, secure, and high-performance data systems.

Key Responsibilities

• Design, build, and optimize cloud-based data platforms supporting enterprise data, analytics, and reporting needs.
• Develop and maintain ETL/ELT pipelines, data ingestion frameworks, and automated data workflows.
• Collaborate with cross-functional teams including data architects, business analysts, and cloud infrastructure teams to deliver integrated data solutions.
• Implement data quality, data validation, and data governance controls across the platform.
• Work with cloud-native technologies (Azure/AWS/GCP) to scale data storage, processing, and compute environments.
• Support production systems, troubleshoot issues, and ensure platform reliability, security, and performance.
• Optimize SQL queries, data models, and high-volume pipelines for efficient processing.
• Participate in platform modernization, migration, and transformation initiatives.

Required Skills & Experience

• Strong hands-on experience as a Cloud Data Engineer / Data Platform Engineer.
• Expertise in at least one major cloud ecosystem — Azure, AWS, or GCP.
• Proficiency in building pipelines using modern data engineering tools (Databricks, Snowflake, Glue, ADF, Airflow, etc.).
• Strong SQL programming and data modeling skills.
• Experience with Python, Spark, or similar technologies for data processing.
• Familiarity with cloud security, IAM, networking, monitoring, and automation.
• Experience working in financial services or banking environments preferred (plus for Mizuho-specific exposure).
• Excellent communication and ability to collaborate in a fast-paced enterprise setting.

Nice-to-Have

• Experience with containerization (Docker/Kubernetes).
• Exposure to real-time data streaming (Kafka, Kinesis, or Pub/Sub).
• Experience with DevOps/CI-CD for data deployments.