Data Engineer
1 week ago
Job Title: AWS Data Engineer
Experience: 8-12 Yrs
Must Have Skills: Client Management, Pyspark, Glue, EMR Cluster, Lamda, DMS, ETL, AWS
Required Skills:
- 8-12 years of experience in Data Engineering
- Creation and maintenance of optimum data pipeline architecture for ingestion, processing of data
- Creation of necessary infrastructure for ETL jobs from a wide range of data sources using, S3, Snowflake and AWS data services
- Experience in Data storage technologies like Amazon S3, SQL, NoSQL
- Hands on experience in writing complex SQL.
- Hands on experience in developing pipelines using AWS data services like Glue, Lambda
- Develop, manage, and optimize data pipelines using AWS Glue and PySpark.
- Hands on experience in Optimizing AWS services for cost-effectiveness and performance.
- Data modeling technical awareness
- Experience in working with stakeholders working in different time zones
Responsibilities:
- Assist in the design and implementation of Snowflake-based analytics solution (data lake and data warehouse) on AWS
- Requirements definition, source data analysis and profiling, the logical and physical design of the data lake and data warehouse as well as the design of data integration and publication pipelines
- Develop Snowflake deployment and usage best practices
- Build and maintain data pipelines adhering to suggested enterprise architecture principles and guidelines
- Design, build, test, and maintain data management systems
- Work in sync with internal and external team members like data architects, data scientists, data analysts to handle all sorts of technical issue.
- Working in Agile/Lean model
- Deliver quality deliverables on time
- Troubleshoot and resolve pipeline and infrastructure issues promptly.
- Able to understand and translate complex functional requirements into technical solutions with the help of product managers/business analysts.
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