Data Architect - Python/PySpark

Description :

Key Responsibilities :

- Design and implement scalable data architectures on AWS and Azure cloud platforms

- Build and manage enterprise-grade data pipelines using Python, PySpark, and DBT

- Develop and optimize ELT workflows using DBT and Snowflake

- Design modern data platforms including Data Lake and Data Warehouse architectures

- Work on Snowflake data modeling, transformation logic, and performance optimization

- Build and maintain Data Lake and Lakehouse architectures using S3 and ADLS

- Develop and manage large-scale ETL/ELT data pipelines

- Lead cloud data migration and modernization initiatives

- Ensure data quality, governance, scalability, and platform performance optimization

- Collaborate with analytics, engineering, and business teams to deliver scalable data solutions

- Mentor junior engineers and contribute to architectural best practices and technical leadership

Required Skills & Experience :

- 8-14 years of experience in Data Engineering / Data Architecture

Strong hands-on expertise in AWS services including :

- S3

- Glue

- Redshift

Experience with Azure services including :

- Azure Data Factory (ADF)

- Azure Data Lake Storage (ADLS)

- Synapse Analytics

- Strong Snowflake experience including data modeling and optimization

- Proficiency in Python and PySpark

- Hands-on experience with DBT including models, macros, and incremental pipelines

- Strong SQL and data modeling expertise

- Experience designing scalable cloud-native data architectures

- Strong understanding of ETL/ELT frameworks and distributed data processing

Preferred Candidate Profile :

- Strong problem-solving and analytical skills

- Experience working on enterprise-scale cloud data transformation projects

- Ability to work collaboratively with cross-functional teams

- Strong communication and technical leadership capabilities

- Passion for modern data engineering and scalable architecture design