Job Description: Data Engineer (PySpark + AWS Glue + Snowflake)

About the Role

We are seeking a highly skilled Data Engineer with expertise in PySpark, AWS Glue, and Snowflake to design, build, and optimize scalable data pipelines. The ideal candidate will have robust problem-solving skills, experience with cloud-based data platforms, and the ability to collaborate across teams to deliver high-quality data solutions.

Key Responsibilities
Data Pipeline Development: Design, implement, and maintain ETL/ELT workflows using PySpark and AWS Glue.
Snowflake Integration: Develop and optimize data models, schemas, and queries in Snowflake.
Data Quality Assurance: Ensure accuracy, consistency, and reliability of data across systems.
Performance Optimization: Tune PySpark jobs and Snowflake queries for efficiency.
Collaboration: Work closely with data scientists, analysts, and business stakeholders to deliver actionable insights.
Documentation: Maintain transparent technical documentation for workflows, processes, and standards.





Required Skills
PySpark: Robust experience in distributed data processing.
AWS Glue: Hands-on expertise in building serverless ETL pipelines.
Snowflake: Proficiency in data warehousing, query optimization, and performance tuning.
SQL: Advanced query writing and optimization skills.
Cloud Platforms: Familiarity with AWS ecosystem (S3, Lambda, IAM, CloudWatch).
Version Control: Experience with Git/GitHub for collaborative development.

Preferred Qualifications
Experience with Data Lake Architecture.
Knowledge of CI/CD pipelines for data workflows.
Exposure to Streaming Data (Kafka, Kinesis).
Strong problem-solving and analytical skills.

Education & Experience
Bachelors or Master’s degree in Computer Science, Information Technology, or related field.
3–6 years of experience in data engineering role.

📌 Data Engineer+python+pyspark Hyderabad
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📍 Hyderabad