Senior Data Analytics Engineer

Job Summary

We are seeking a highly skilled Data Engineer to join our global organization. The ideal candidate will have a minimum of 5 years of experience in data engineering, with a strong background in Spark, Python, Azure Databricks, SQL, and Scala. The role involves working within a global team, leveraging cloud platforms like Azure or GCP, and contributing expertise to multiple projects.

• Develop and maintain scalable data pipelines using Spark, Python, and Scala within Azure Databricks or similar cloud-based environments.
• Collaborate with cross-functional teams across the globe to understand data requirements and implement efficient solutions.
• Utilize SQL and other querying languages to manipulate and extract data from various sources, ensuring accuracy and efficiency.
• Design, build, and optimize data models and architectures to support data processing and analytics needs.
• Ensure data quality, integrity, and security while adhering to best practices and compliance standards.
• Work closely with stakeholders to understand business needs and translate them into technical requirements for data solutions.
• Mentor and guide junior team members, fostering a collaborative and knowledge-sharing environment.
• Communicate effectively with global teams, providing updates, insights, and support as needed.
• Bachelor's or master's degree in computer science, Engineering, or a related field.
• 5+ years of hands-on experience as a Data Engineer, preferably in a global organization.
• Proficiency in Spark, Python, Azure Databricks, SQL, and Scala.
• Experience working with cloud platforms such as Azure or GCP, leveraging their data services.
• Strong understanding of data modeling, ETL processes, and data warehousing concepts.
• Ability to work effectively in a global, multicultural team environment, across different time zones.
• Proven track record of delivering on multiple projects with a focus on scalability, reliability, and performance.
• Excellent problem-solving skills and a proactive approach to tackling complex data challenges.
• Knowledge of life insurance industry preferred.