Data Platform Engineer

About the Opportunity

Join a global technology organization delivering enterprise-scale cloud and data transformation solutions for international clients. As a Data Platform Engineer, you will design, build, and optimize modern cloud-native data platforms that enable advanced analytics, artificial intelligence (AI), machine learning (ML), and business intelligence (BI).

You will work with cross-functional teams across multiple regions to develop secure, scalable, and high-performance data solutions using leading cloud technologies and modern data engineering practices.

Key Responsibilities

• Design, develop, and maintain enterprise data platforms in cloud and hybrid environments.
• Build scalable ETL/ELT pipelines to ingest, transform, and process structured, semi-structured, and unstructured data.
• Develop and optimize data lakes, data warehouses, and lakehouse architectures.
• Implement data integration solutions across enterprise applications and third-party systems.
• Ensure data quality, governance, lineage, metadata management, and security compliance.
• Optimize database performance, query execution, and storage efficiency.
• Deploy and manage cloud-based analytics platforms.
• Automate infrastructure provisioning using Infrastructure as Code (IaC).
• Implement CI/CD pipelines for data engineering workflows.
• Monitor platform health, troubleshoot production issues, and ensure high availability.
• Collaborate with Data Scientists, BI Developers, Software Engineers, Cloud Engineers, and business stakeholders.
• Support enterprise cloud migration and modernization initiatives.
• Follow Agile/Scrum delivery methodologies and DevOps best practices.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline.
• 4–10+ years of experience in Data Engineering, Data Platform Engineering, or Cloud Data Engineering.
• Strong proficiency in SQL and relational database concepts.
• Hands-on experience with Python or Scala.
• Experience designing and developing enterprise ETL/ELT pipelines.
• Strong understanding of data modeling, dimensional modeling, and data architecture.
• Experience working in Agile development environments.

Data Platform Engineer, Cloud Data Engineer, Data Engineer, Azure Data Engineer, AWS Data Engineer, GCP Data Engineer, Databricks, Snowflake, Microsoft Fabric, Azure Synapse, Spark, SQL, Python, ETL, ELT, Data Warehouse, Data Lake, Lakehouse, Apache Airflow, Kafka, Kubernetes, Docker, Terraform, CI/CD, DevOps, DataOps, Big Data, Analytics Engineer, Permanent, Global Technology Company.