Job Description
| Role: |
Lead Data Engineer - AWS |
| Experience: |
4 - 7 Years |
| Location: |
Gurugram |
| 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.
-
4-7 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
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