Senior Data Engineer - AWS in Bangalore, भारत

Position : Senior Data Engineer (AWS)Overall/Total Experience : 4 - 8 yearsLocation : BengaluruWorking Days : 5 Days from OfficeNotice Period Requirement : Immediate Joiners/Serving Notice Period OnlyClient's Company Size : Startup / Small EnterpriseRoles & Responsibilities :- Create and maintain optimal data pipeline architecture for ETL/ELT into structured data.- Assemble large, complex data sets that meet business requirements and create multi-dimensional modelling like Star Schema and Snowflake Schema.- Expert level experience in creating scalable data warehouse including Fact tables, Dimensional tables and ingest datasets into cloud-based tools.- Identify, design, and implement internal process improvements including automating manual processes and optimising data delivery.- Collaborate with stakeholders to ensure seamless integration of data with internal data marts, enhancing advanced reporting.- Setup and maintain data ingestion, streaming, scheduling, and job monitoring automation using AWS services including Lambda, Code Pipeline, Glue, S3, and Redshift.- Build analytics tools that utilize the data pipeline to provide actionable insight into customer acquisition and operational efficiency.- Utilize GitHub for version control, code collaboration, and repository https://jobeax.com/link/ieR2UQ5cXUcxBtsX Requirements :- Must have at least 4+ years of hands-on data engineering experience with the recent 2+ years in AWS cloud data warehouses and AWS cloud services.- Must have advanced SQL knowledge and hands-on experience with relational databases and query authoring, plus a cloud data warehouse like AWS Redshift.- Must have expert-level experience creating scalable data warehouses - Fact tables, Dimensional tables, and ingesting datasets into cloud-based tools.- Must have strong multi-dimensional data modelling experience - Star Schema, Snowflake Schema, normalisation/de-normalisation, joins, OLAP cube modelling, and schema evolution while maintaining data integrity.- Must have hands-on experience creating and maintaining optimal ETL/ELT data pipeline architecture into structured data.- Must have experience setting up and maintaining data ingestion, streaming, scheduling, and job-monitoring automation using AWS services - Lambda, Glue, S3, Redshift, and Code Pipeline (CI/CD).- Must have experience building and optimizing big-data pipelines, architectures, and datasets, including data compression into PARQUET and SQL performance tuning. (ref:hirist.tech)