Job Description
Roles and Responsibilities
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- Create and maintain optimal data pipeline architecture for ETL/ELT into structured datan
- Assemble large, complex data sets that meet business requirements and create multi-dimensional modelling like Star Schema and Snowflake Scheman
- Expert level experience in creating scalable data warehouse including Fact tables, Dimensional tables and ingest datasets into cloud-based tools.n
- Identify, design, and implement internal process improvements including automating manual processes and optimizing data deliveryn
- Collaborate with stakeholders to ensure seamless integration of data with internal data marts, enhancing advanced reporting.n
- Setup and maintain data ingestion, streaming, scheduling, and job monitoring automation using AWS services including Lambda, Code Pipeline, Glue, S3, and Redshift.n
- Build analytics tools that utilize the data pipeline to provide actionable insight into customer acquisition and operational efficiency.n




- Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs.n
- Utilize GitHub for version control, code collaboration, and repository managementn
- Create data tools for analytics and data scientist team membersn
- Ensure data privacy and compliance with relevant regulations when handling customer data.n
- Maintain data quality and consistency within the applicationn

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nRequirements
n1Strong Senior Data Engineer Profile with AWS data-warehousing and pipeline expertise
n2Mandatory (Experience): 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
n3Mandatory (Tech skill 1): Must have advanced SQL knowledge and hands-on experience with relational databases and query authoring, plus a cloud data warehouse like AWS Redshift.
n4Mandatory (Tech skill 2): Must have expert-level experience creating scalable data warehouses —

📌 Senior Data Engineer (Bengaluru)
🏢 DataZymes
📍 Bengaluru