Lead Data Engineer (AWS)

Role: Lead Data Engineer - AWS

Experience:

8+ Years

Work Mode:

Hybrid

Key Role and Responsibilities:

• Understand and translate business needs into data models supporting long-term solutions.
• Perform reverse engineering of physical data models from databases and SQL scripts.
• Analyze data-related system integration challenges and propose appropriate solutions.
• Assist with and support setting the data architecture direction (including data movement approach, architecture/technology strategy, and any other data-related considerations to ensure business value)
• Design and implement data pipelines, Optimize data processing and storage, Ensure data solutions meet performance standards, Provide technical support, Collaborate with stakeholders.

Must Have:

• 8+ Years of experience as a Data Engineer
• Strong technical expertise in SQL Advanced SQL querying skills (joins, subqueries, CTEs, aggregation)
• Strong knowledge of joints and common table expressions (CTEs)
• Strong experience with Python
• Experience in Snowflake, ETL, SQL, CI/CD
• Strong expertise in ETL process and with various data model concepts
• Knowledge of Star Schema and snowflake schema
• Good to know about AWS services such as S3, Athena, Glue, EMR/Spark with a major emphasis on S3 and Glue.

Good-to-Have Skills:

• Experience with Big Data Tools and technologies
• Good Understanding of data structures and data analysis
• Knowledge of Insurance Domain is an addition.

Qualifications:

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.

7+ years of experience in data engineering roles using AWS and Snowflake.

Strong problem-solving, communication, and collaboration skills.

Education:

Bachelor’s or master’s degree in computer science, Engineering, or related field.

Key Skills:

AWS, Python, Snowflake, Glue, S3, SQL