Senior Data Engineer

On a typical day, you will design and manage scalable cloud-based data infrastructure while building high-performance ETL pipelines and data warehouses to support analytics. You ll collaborate with multi-functional teams to integrate diverse data sources and automate workflows for real-time processing. Additionally, you will monitor and optimize data pipelines for performance and cost efficiency, mentor junior engineers, and ensure compliance with data security and governance regulations. Staying updated on the latest cloud technologies will also be a key part of your role.

How You ll Make an Impact

• Design, implement, and manage scalable, secure cloud-based data infrastructure on platforms like AWS, GCP, and Azure. Build and maintain high-performance ETL pipelines, data lakes, and warehouses for analytics and reporting.
• Architect and optimize cloud storage solutions using Azure Blob Storage, Amazon S3, Google Cloud Storage, and data warehouses like Redshift, BigQuery, or Snowflake.
• Integrate diverse data sources to build unified, high-quality data platforms. Collaborate with architects, data scientists, and business teams to craft data models and analytical solutions in the cloud.
• Automate data workflows for real-time and batch processing using tools like Azure Data Factory, AWS Lambda, or Google Cloud Dataflow.
• Manage and optimize Azure SQL Database, Cosmos DB, and other databases for high availability and performance. Supervise and optimize data pipelines for efficiency and cost management. Implement data security and governance practices in compliance with regulations (GDPR, HIPAA) using Azure security features.
• Mentor junior data engineers on Azure services, data pipeline development, and coding techniques. Implement supervising solutions to ensure data pipeline reliability and maintain clear user documentation.
• Ensure high availability and disaster recovery for critical data services. Conduct performance tuning and troubleshooting of cloud-based data systems. Stay updated on cloud technologies and data engineering trends to enhance existing systems.

What You Bring

• For our Onshore Execution Digital Product Development team, we are looking for a Senior Cloud Data Engineer with more than 10 years of experience. In this role, you will be responsible for designing, building, and maintaining scalable, high-performance data systems and pipelines in the cloud.
• You will leverage cloud technologies to build data infrastructure and solutions that support analytics, business intelligence, and machine learning at scale.
• You ll work closely with cross-functional teams to help transform data into actionable insights while ensuring optimal performance, security, and scalability.
• Bachelor s or master s degree in computer science, engineering, or a related field (or equivalent experience with 7+ years of data engineering experience, with at least 3 years in cloud environments (preferably Azure). Expertise in designing and optimizing cloud data systems and pipelines.
• Strong proficiency in programming languages like C#, Python, Scala, or SQL.
• Deep experience with cloud data warehousing platforms (Snowflake, Amazon Redshift, Google BigQuery). Hands-on experience with cloud storage solutions (Azure Blob Storage, Amazon S3, Google Cloud Storage).
• Solid understanding of cloud computing concepts and infrastructure as code (Terraform, Cloud Formation). Expertise in data modeling, architecture, and pipeline automation and Familiarity with data governance, security, and compliance in cloud environments.
• Proven experience with containerization and orchestration technologies (Docker, Kubernetes) and Solid understanding of supervising and troubleshooting tools.
• Ability to collaborate with multi-functional teams and communicate technical solutions to non-technical partners.
• Preferred to have certifications in cloud platforms (AWS Certified Solutions Architect, Google Professional Data Engineer, Azure Data Engineer). Experience with real-time data streaming platforms (Apache Kafka, Amazon Kinesis). Knowledge of CI/CD pipelines and DevOps practices in data engineering workflows