About Position:

Experienced AWS Architect with expertise in building scalable data pipelines, processing large datasets, and developing cloud-based data solutions using Databricks, PySpark, Python, SQL, and AWS technologies. Skilled in ETL/ELT development, data transformation, performance optimization, and cloud data architecture. Relevant enterprise profiles and resumes show experience in Databricks-based data processing, PySpark transformations, SQL development, and AWS cloud services.

Role: AWS Architect
Location: All Persistent Location
Experience: 12+ years
Job Type: Full-Time Employment

What You'll Do:

Design, develop, and maintain scalable ETL/ELT data pipelines.
Process and transform large volumes of structured and unstructured data using PySpark and Databricks.
Develop productive data solutions using Python and SQL.
Build and manage cloud-native data platforms on AWS (S3, EC2, Lambda, etc.).
Optimize data workflows, Spark jobs, and database performance.
Collaborate with business stakeholders to understand requirements and deliver analytics-ready datasets.




Implement data quality, governance, monitoring, and performance best practices.
Support data warehousing, reporting, and advanced analytics initiatives.

Expertise You'll Bring:

Strong hands-on experience with Databricks for data engineering and large-scale data processing.
Advanced proficiency in PySpark for distributed data transformation and analytics.
Solid programming skills in Python for automation, data pipelines, and backend processing.
Expertise in SQL for data modeling, query optimization, and reporting.
Experience with AWS services such as S3, EC2, Lambda, and cloud-based data architectures.
Knowledge of Spark optimization, Delta Lake, ETL frameworks, and data lake concepts.
Ability to build reliable, high-performance, and scalable data platforms.
Strong problem-solving skills with a focus on performance, reliability, and business outcomes.

Benefits:

Competitive salary and benefits package

📌 AWS Architect (Pune)
🏢 Persistent Systems
📍 Pune