Position : Senior Data Engineer (AWS)

Overall/Total Experience : 4 - 8 years

Location : Bengaluru

Working Days : 5 Days from Office

Notice Period Requirement : Immediate Joiners/Serving Notice Period Only

Client's Company Size : Startup / Small Enterprise

Roles & 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 management.

Candidate 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.