Lead Data Engineer

Responsibilities:  

• Lead the design, development, and implementation of data solutions using AWS and Snowflake.  

• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.  

• Develop and maintain data pipelines, ensuring data quality, integrity, and security.  

• Optimize data storage and retrieval processes to support data warehousing and analytics.  

• Provide technical leadership and mentorship to junior data engineers.  

• Work closely with stakeholders to gather requirements and deliver data-driven insights.  

• Ensure compliance with industry standards and best practices in data engineering.  

• Utilize knowledge of insurance, particularly claims and loss, to enhance data solutions.  

Requirements:  

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.  

• Proven experience as a Data Engineer, with a focus on AWS and Snowflake.  

• Strong understanding of data warehousing concepts and best practices.  

• Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.  

• Experience in the insurance industry, preferably with knowledge of claims and loss processes.  

• Proficiency in SQL, Python, and other relevant programming languages.  

• Strong problem-solving skills and attention to detail.  

• Ability to work independently and as part of a team in a fast-paced environment.  

• Experience with data modelling and ETL processes.  

• Familiarity with data governance and data security practices.  

• Certification in AWS or Snowflake is a plus. 

 Must have:  

• 6-8 years of relevant experience in Data Engineering and delivery.   

• 5+ years of relevant work experience in Big Data Concepts. Worked on cloud implementations.   

• Strong experience with SQL, python and Pyspark   

• Good understanding of Data ingestion and data processing frameworks    

• Good experience in Snowflake, SQL, AWS (glue, EMR, S3, Aurora, RDS, AWS architecture)   

• Good aptitude, strong problem-solving abilities, analytical skills, and ability to take ownership as appropriate.   

• Should be able to do coding, debugging, performance tuning, and deploying the apps to the Production environment.   

• Experience working in Agile Methodology   

Good to have:       
Have experience in DevOps tools (Jenkins, GIT etc.) and practices, continuous integration, and delivery (CI/CD) pipelines.   
Worked on cloud implementations, data migration, Data Vault 2.0, etc.