Description

1.End to End Ownership of Data Pipelines

Designs, builds, and operates critical batch and streaming pipelines (Glue, Redshift, Spark, Kinesis, Lambda), handling complex edge cases like schema evolution, CDC, late data, and high-volume workloads.

2.Data Architecture & Modeling

Owns the data architecture for a specific business domain, defining Lakehouse patterns, data models, partitioning strategies, and storage/query choices (S3, Redshift, Athena) based on real usage and performance needs aligning with Enterprise standards.

3.Hands On AWS Optimization & Troubleshooting

Actively tunes Spark jobs, Glue configurations, Redshift performance, and S3 layouts; investigates production issues, reduces pipeline latency, and controls cloud cost through code and configuration changes.

4.Production Reliability, Quality & Security

Implements domain level data quality checks, monitoring, and alerting; ensures secure access; owns production incidents and drives permanent fixes.

5.Technical Leadership Within the Team

Leads by example through coding, PR reviews, and design guidance; mentors senior engineers, sets engineering standards, and translates business requirements into scalable, reliable data solutions

Key Skills

Education

Any Gradute