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.