Engineer

Skill: AWS Data Engineer

• Must have AWS Glue, Lambda, Athena, Pyspark, Redshift, EMR, AWS RDB, AWS DynamoDB, AWS Glacier, Python.

Experience Required:

• Minimum 5 years of professional experience in data integration and management.

• 3+ years of hands on development experience in AWS Glue, Lambda functions, AWS Athena, Redshift, Pyspark.

• Hands on working experience in AWS GLUE ETL tool and having good knowledge on any of the ETL tools(Informatica cloud,Talend etc.).

• Must have working experience with SQL, and databases (e.g.: Postgres, Redshift) implementing Data Models.

• Expertise with Python Language and Apache Spark. Have working experience in projects involving these.

• Strong hands on exposure to AWS Analytics services particulary Lambda,Step functions,EMR, Athena, Glue, Data-Pipelines.

• Understanding and technical knowledge on AWS service like EC2, S3. Should have used these technologies in previously executed projects.

• Strong AWS development experience for data ETL/pipeline/integration/automation work. Should have a deep understanding of BI & Analytics Solution development lifecycle.

• Full Flexed in AWS cloud development & Automation for Analytics. Should have a deep understanding of AWS Services (Redshift, Glue, Lambda, Athena, S3, EC2), Visual Studio, SQL Server, SSIS, Matillion; Python.

• Strong experience on real-time scalable workflow implementation.

Responsibilities:

• Developer will be part of an Agile Development team focusing on Sprint Agile implementation.

• Developer will be developing data ingestion pipelines from heterogenous sources like databases, Files, APIs, Kafka streaming etc using a variety of services.

• Developer may be assigned to deliver the data from AWS data platform for different consumption use cases and services.

• Developer may be engaged in peer reviews to ensure code accuracy and well architected architecture and implementation.

• Developer may be asked to do client demo or another project demo.

• Developer must be proactive in escalating impacting issues and be resourceful to look for alternative.

• Developer may have to work on tight timelines sometimes.

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