Kodehash - Lead Data Engineer - Python

3 weeks ago


gurugram, India Kodehash Technologies Pvt Ltd Full time

Job Description :

The Data Engineer will play a key role in greenfield development of Inbound data flow and integration to Strategic data warehouse along with delivery of Backlog, Mandatory book of work, minor enhancements to current platform.

Key Responsibility for the Role :

- Design, develop, and maintain data pipelines to ingest, transform, and load data from various sources into cloud Data Warehouse such as Snowflake.

- Implement ETL (Extract, Transform, Load) processes using Snowflake's features such as Snowpipe, Streams, and Tasks.

- Optimize data warehouse performance and scalability using SQL features like clustering, partitioning, and materialized views.

- Implement data quality framework to ensure consistency and accuracy of data across different systems.

- Work on data modeling - roles, databases, schemas, ETL tools with cloud-driven skills.

- Strong handle on SQL language and cloud-based data warehouse.

- Work on Data Masking / Encryption / Tokenization, Data Wrangling / Data Pipeline orchestration (tasks).

- Setup AWS S3/EC2, Configure External stages, and SQS/SNS.

Key Skills for the Role :

- Must have 6-10 Years of experience.

- SQL - Strong SQL skills for querying and data manipulation.

- ETL - Experience with ETL processes for data integration.

- Python - Strong command of Python, especially in AWS Boto3, JSON handling, and dictionary operations.

- Unix - Competent in Unix for file operations, searches, and regular expressions.

- AWS - Proficient with AWS services including EC2, Glue, S3, Step Functions, and Lambda for scalable cloud solutions.

- Database Modeling - Solid grasp of database design principles, including logical and physical data models, and change data capture (CDC) mechanisms.

- Snowflake - Experienced in Snowflake for efficient data integration, utilizing features like Snowpipe, Streams, Tasks, and Stored Procedures.

- Airflow - Fundamental knowledge of Airflow for orchestrating complex data workflows and setting up automated pipelines.

(ref:hirist.tech)

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