Lead Data Engineer

Key Skills: Snowflake, SQL, Python, Spark, AWS- Glue, Big Data Concepts

Must have:

• 10+ years of relevant experience in Data Engineering and delivery.

• 10+ 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.

Requirements:

• Bachelors or Masters 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.

Preferred Qualifications:

• Experience with data modeling and ETL processes.

• Familiarity with data governance and data security practices.

• Certification in AWS or Snowflake is a plus.