AWS Pysark Developer

Saama Technologies; Pune District; Hybrid; INR 900,000 - 1,500,000; Full time

Job summary

Saama Technologies in Pune seeks a Strong AWS PySpark Developer to design and optimize scalable AWS data pipelines, leveraging PySpark, SQL, and Agile practices to maintain high data quality.

You will work across the data engineering lifecycle, implementing ETL with EMR, Glue, and DataBrew, and optimizing performance via Spark tuning and serverless Lambda.

Qualifications

• 4-6 years hands-on experience in Data Engineering, Big Data, or Cloud Architecture
• Proven Python & AWS expertise as an AWS Data Engineer
• Deep PySpark mastery and experience optimizing heavy PySpark workloads
• Strong experience with core AWS data services: EMR, Glue, DataBrew, Lambda, Redshift

Responsibilities

• Design and implement large-scale, high-performance data pipelines on AWS
• Work in Waterfall/Hybrid Agile teams using JIRA and manage backlogs and dashboards
• Provide daily, weekly and monthly reporting to keep offshore and onshore leads informed
• Ensure data quality and implement data lineage across enterprise workflows
• Optimize PySpark workloads and SQL performance for distributed databases
• Architect serverless data pipelines using AWS Lambda and event-driven architectures
• Model, manage, and optimize data warehousing in AWS Redshift for analytics
• Leverage AI coding tools (Copilot, Claude Code) to accelerate development timelines

Skills

PySpark

Python

AWS

SQL

Data Engineering

JIRA

Git

GitHub Actions

AI Tools

Spark optimization

Tools

AWS EMR

AWS Glue

AWS DataBrew

AWS Lambda

AWS Redshift

S3

IAM

Step Functions

Apache Airflow

Terraform

Job description

We need a Strong AWS PySpark Developer for our data engineering team. You will design and optimize scalable AWS data pipelines, leveraging expertise in distributed processing, PySpark, SQL, and Agile methodologies to maintain high data quality standards.

Key Responsibilities

• Data Pipeline Architecture & ETL: Build / Implement large-scale, high-performance data pipelines using various AWS Services like AWS EMR, PySpark, AWS Glue, and AWS DataBrew.
• Work in Waterfall / Hybrid Agile Teams using JIRA, Actively participate in planning and managing the backlog and leveraging JIRA reporting/dashboards to track team velocity, bottlenecks, and project health.
• Reporting : Daily, Weekly and Monthly reporting to ensure Offshore and Onshore leads are fully informed and engaged.
• Data Governance & Quality: Build solutions that guarantee high Data Quality and implement comprehensive Data Lineage tracking across all enterprise data workflows.
• Performance Optimization: Apply advanced PySpark optimization techniques (handling data skewness, memory management, partitioning, and broadcasting) and rigorous SQL optimization.
• Serverless Data Processing: Architect and deploy event-driven data workflows and microservices utilizing AWS Lambda.
• Data Warehousing: Model, manage, and optimize data storage and querying within AWS Redshift for analytical reporting and BI consumption.
• Accelerated Delivery: Utilize AI coding assistants (such as GitHub Copilot and Claude Code) to streamline development, improve code quality, and accelerate project delivery timelines.

Required Qualifications & Skills

• Experience: Minimum of 4-6 years of hands‑on experience in Data Engineering, Big Data, or Cloud Architecture
• Python & AWS Expertise: Proven experience operating as an AWS Data Engineer using Python (Active AWS certifications are highly preferred).
• PySpark Mastery: Exceptional proficiency in Python and Apache Spark. Must have a deep understanding of Spark's internal workings and hands‑on experience optimizing heavy PySpark workloads.
• AWS ETL Ecosystem: Strong, demonstrated experience with core AWS data services including AWS EMR, AWS Glue, AWS DataBrew, AWS Lambda, and AWS Redshift.

AWS S3, IAM, and AWS Step Functions.

• SQL & Database Skills: Advanced SQL proficiency with a track record of tuning complex queries for performance across distributed databases.
• Agile & JIRA: Demonstrated experience driving Agile methodologies. Must be well‑versed in JIRA, specifically in configuring workflows and generating detailed JIRA reports for stakeholders.
• DevOps & CI/CD: Strong proficiency in version control and DevOps practices using Git and GitHub Actions for automated CI/CD pipelines.
• AI‑Assisted Development: Demonstrated experience successfully integrating AI tools (Copilot, Claude Code) into daily engineering workflows to boost productivity.

Nice to Have

• Experience with workflow orchestration tools like Apache Airflow.
• Knowledge of Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormation.