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.