Job Description
About Position:
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nExperienced 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.
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- Role: AWS Architectn
- Location: All Persistent Locationn
- Experience: 12+ yearsn
- Job Type: Full-Time Employmentn

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nWhat You'll Do:
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- Design, develop, and maintain scalable ETL/ELT data pipelines.n
- Process and transform large volumes of structured and unstructured data using PySpark and Databricks.n
- Develop effective data solutions using Python and SQL.n
- Build and manage cloud-native data platforms on AWS (S3, EC2, Lambda, etc.).n
- Optimize data workflows, Spark jobs, and database performance.n




- Collaborate with business stakeholders to understand requirements and deliver analytics-ready datasets.n
- Implement data quality, governance, monitoring, and performance best practices.n
- Support data warehousing, reporting, and advanced analytics initiatives.n

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