Data Engineering Architect – Manager

Role Overview

• Design and implement scalable Data Lakehouse architectures on AWS
• Build and optimize data warehouse solutions using Amazon Redshift and Snowflake
• Develop and manage ETL/ELT pipelines using PySpark and AWS Glue
• Design Fact and Dimension data models for analytics workloads
• Optimize SQL queries, data distribution, and partition strategies
• Process and transform structured and semi-structured data using PySpark
• Manage data transformation workflows using DBT
• Ensure data quality, performance, and reliability across data pipelines
• Work with BI tools such as Tableau or Power BI for reporting and analytics
• Collaborate with data engineers, analysts, and business teams to deliver scalable data solutions

Requirements

• 10+ years of experience in data engineering
• Strong knowledge of Amazon Redshift and Snowflake data warehouse architectures
• Understanding of MPP architecture, distribution keys, and sort keys
• Hands-on experience with PySpark and Spark SQL
• Experience handling JSON data, partitioning, and Spark transformations
• Knowledge of AWS Glue, DynamicFrame, and incremental data processing
• Experience with DBT including macros, Jinja templating, and incremental models
• Understanding of data warehouse concepts such as Fact and Dimension tables
• Experience working with BI tools such as Tableau or Power BI.

Tech Stack

• Amazon Redshift
• AWS
• ETL
• PySpark
• Spark
• SQL
• Tableau

Benefits

• Opportunity to work on large-scale cloud data transformation initiatives.
• Flexible remote work model from India
• Exposure to enterprise clients across the East Coast region.
• Growth-oriented leadership culture.