Senior Data Engineer, Upto $12k
Posted Updated
We are looking for an experienced
Senior Data Engineer
to join a Data & Analytics team and contribute to the development of scalable, enterprise-grade data platforms. This role will focus on designing and maintaining data pipelines, implementing modern lakehouse solutions, and enabling data-driven decision-making across the organization. Key Responsibilities
Design, build, and maintain ETL/ELT data pipelines using Python and PySpark. Develop and manage lakehouse/data lake architectures, including data modeling, partitioning, and metadata management. Deploy and support containerized data solutions using Kubernetes and Docker. Optimize SQL Server databases, data models, and query performance. Implement CI/CD practices, automated testing, and monitoring for data platforms. Ensure data governance, security, and compliance standards are met. Collaborate with cross-functional teams to deliver trusted and scalable data solutions. Provide technical guidance, perform code reviews, and support continuous improvement initiatives. Requirements
At least 5 years of hands-on experience in data engineering, ETL/ELT development, or related fields. Strong expertise in SQL Server, including performance tuning and optimization. Advanced Python programming skills and experience with PySpark. Experience with Kubernetes, Docker, and modern DevOps practices. Knowledge of data modeling, lakehouse/data lake architectures, and Apache Iceberg. Experience with workflow orchestration tools such as Apache Airflow. Hands-on experience with NoSQL databases (e.g., MongoDB, Cassandra). Understanding of data security, governance, and access control principles. Strong analytical, problem-solving, and stakeholder management skills. Degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent practical experience. Short listed candidates will be notified EA Registration Number: R22106307 Business Registration Number: 200611680D. License Number: 10C5117
Senior Data Engineer
to join a Data & Analytics team and contribute to the development of scalable, enterprise-grade data platforms. This role will focus on designing and maintaining data pipelines, implementing modern lakehouse solutions, and enabling data-driven decision-making across the organization. Key Responsibilities
Design, build, and maintain ETL/ELT data pipelines using Python and PySpark. Develop and manage lakehouse/data lake architectures, including data modeling, partitioning, and metadata management. Deploy and support containerized data solutions using Kubernetes and Docker. Optimize SQL Server databases, data models, and query performance. Implement CI/CD practices, automated testing, and monitoring for data platforms. Ensure data governance, security, and compliance standards are met. Collaborate with cross-functional teams to deliver trusted and scalable data solutions. Provide technical guidance, perform code reviews, and support continuous improvement initiatives. Requirements
At least 5 years of hands-on experience in data engineering, ETL/ELT development, or related fields. Strong expertise in SQL Server, including performance tuning and optimization. Advanced Python programming skills and experience with PySpark. Experience with Kubernetes, Docker, and modern DevOps practices. Knowledge of data modeling, lakehouse/data lake architectures, and Apache Iceberg. Experience with workflow orchestration tools such as Apache Airflow. Hands-on experience with NoSQL databases (e.g., MongoDB, Cassandra). Understanding of data security, governance, and access control principles. Strong analytical, problem-solving, and stakeholder management skills. Degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent practical experience. Short listed candidates will be notified EA Registration Number: R22106307 Business Registration Number: 200611680D. License Number: 10C5117