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Role** AWS Data Engineer
Required Technical Skill Set** AWS
Desired Experience Range** 5+ years
Location of Requirement Mumbai (Preferred) but Open for Pan India
Desired Competencies (Technical/Behavioral Competency)
Must-Have**
(Ideally should not be
more than 3-5) 1. AWS tools (Redshift, Glue, EMR, Athena, StepFunction, CloudFormation, CloudWatch) 2. Programming language -SQL, Python, Pyspark 3. Data Pipelining skills – Data blending 4. Big data technologies- Hadoop, Hive
Good-to-Have 1. Experience working with ETL Integration Tools - SSIS, Informatica 2. Data Science tooling – R, SAS 3. Experience of MPP (Massive Parallel Processing) databases – e.g. Teradata, Netezza 4. Data Management experience – e.g. Data Quality, Security, etc
Expectations from the Role
1 The role will require deep knowledge of data engineering techniques to create data pipelines and build data assets to meet reporting requirements and deliver use cases for the business.
2 Work as part of an Agile software delivery team; typically delivering within an Agile Scrum framework.
3 Analyse data sources, data structure and combine data from multiple sources into a functioning dataset and can publish to visualisation tools
4 Develop solutions based on best practices by promoting reuse, leveraging design patterns, etc
5 Review technical/functional specifications for each use case pipeline with technical teams for new data ingestion from source systems, following the project standards
Job ID: 148989547
Skills:
Aws Redshift, Hadoop Ecosystem, Pyspark, Apache Spark, Data Warehouse, Sql, Hive, Python Programming, Data Protection, Aws Redshift, Airflow, ETL processes, Database technologies for OLTP and OLAP
Skills:
Python (pandas, SQL Alchemy), Pyspark, Sql, boto3, AWS Data Services

Skills:
snowflake , S3, Pyspark, Apache Spark, Redshift, Sql, Lambda, Spark, Data Lake, Python, AWS, Etl, Copilot, Claude, AI coding assistants, Glue
Skills:
Pyspark, Sql, AWS, Data-bricks
Skills:
Sql, Aws Redshift, cloud computing concepts, data modeling and schema design, AWS ecosystem, data warehousing concepts and best practices, ETL ELT processes
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