Aws Data Engineer

About the Role :

Data engineer

Specialization :

Key Responsibilities :

JD: Job Description: Data Engineer (Python, PySpark, AWS)

Role Overview

We are looking for a skilled Data Engineer with strong expertise in Python, PySpark, AWS, and Informatica IICS to design and implement scalable data pipelines, manage cloud-based data solutions, and support enterprise integration needs. The role involves working with large datasets, optimizing ETL workflows, and ensuring high-quality data delivery across systems.

Key Responsibilities

Develop and maintain data pipelines using Python and PySpark for batch and real-time processing.

Design and implement ETL workflows using Informatica IICS (Cloud Data Integration, Application Integration).

Build and optimize AWS-based data solutions (S3, Glue, EMR, Redshift, Lambda, Step Functions).

Ensure data quality, validation, and transformation across multiple sources and destinations.

Collaborate with business and technical teams to gather requirements and deliver solutions.

Perform debugging, performance tuning, and production support for data pipelines and integrations.

Required Skills

Strong programming skills in Python and PySpark for data engineering.

Hands-on experience with AWS services (S3, Glue, EMR, Redshift, Lambda).

Proficiency in Informatica IICS for ETL and integration workflows.

Solid knowledge of SQL and relational databases.

Experience with data governance, data quality frameworks, and troubleshooting.

Preferred Skills

Familiarity with IDQ (Informatica Data Quality) for cleansing and deduplication.

Exposure to big data ecosystems (Hadoop, Spark clusters).

Knowledge of CI/CD pipelines and DevOps practices for data engineering.

Informatica or AWS certifications.

Qualifications

Bachelors degree in Computer Science, Engineering, or related field.

8+ years of experience in data engineering with Python, PySpark, AWS, and IICS.

Strong analytical, communication, and problem-solving skills.