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Data Engineer - SQL/PySpark (4-10 yrs)

4-10 years

Data Engineer - SQL/PySpark (4-10 yrs)

Elements

posted 2mon ago

Job Role Insights

Flexible timing

Job Description

Key Responsibilities :

- Design, develop, and optimize scalable data processing pipelines using Spark and PySpark.

- Implement Spark optimization techniques to enhance performance and efficiency.

- Develop and execute complex SQL queries for data manipulation and transformation.

- Collaborate closely with data scientists, analysts, and engineering teams to address data needs.

- Work with AWS Cloud services such as Redshift, AWS Glue, SQL Server, and Databricks.

- Use Python for data processing tasks, ensuring modularization, packaging, and reusability.

- Basic knowledge of Informatica for data integration.

- Engage in real-time data streaming and integration with tools like NiFi, Kafka, and EventHub (preferred but optional).

- Hands-on experience with Snowflake for data warehousing and analytics.

Required Skills :

- Spark Expertise : Proven experience in Spark and PySpark, including optimization techniques.

- Complex SQL : Strong knowledge of SQL and hands-on experience with complex data processing.

- Cloud Exposure : Familiarity with AWS services (Redshift, Glue, etc.) and Databricks.

- Python Proficiency : Expertise in Python for data processing, scripting, and automation.

- Data Streaming : Experience with NiFi, Kafka, and EventHub is a plus.

- Informatica : Basic understanding of Informatica tools and their integration with other systems.

- Snowflake : Hands-on experience with Snowflake for data warehousing and analytics.


Functional Areas: Software/Testing/Networking

Read full job description

What people at Elements are saying

What Elements employees are saying about work life

based on 19 employees
64%
73%
62%
75%
Flexible timing
Monday to Saturday
No travel
Day Shift
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Elements Benefits

Free Transport
Child care
Gymnasium
Cafeteria
Work From Home
Free Food +6 more
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