Mandatory Skills:

Python, Apache Spark, Data Quality & Validation, PySpark, SQL, Amazon Kinesis, Apache Kafka, Databricks Workflows, Delta Lake on Databricks

Additional Skills:

AWS S3 + Amazon Aurora + DynamoDB, AWS Glue, AWS Redshift, Data Governance Frameworks, GitHub

Key Responsibilities

- Design scalable data engineering solutions using PySpark and modern distributed data processing frameworks.
- Define data ingestion, transformation, and processing architectures aligned with business and analytical objectives.

Behavioral Competencies

- Demonstrates robust ownership while driving data engineering excellence.
- Collaborate effectively with various teams and business stakeholders to ensure smooth delivery.

Must Have

- Python & Advanced SQL
• Spark / distributed processing / PySpark
• Cloud platforms (AWS) Modules like Lambda, Glue, EMR, Dynamo DB, S3, Redshift, EC2, RDS, Step Functions, Cloud Watch, Systems Manager, Event Bridge, DMS
• SSIS and experience with C# scripting
• Data pipeline automation

Nice to have
• Kafka/Kinesis streaming
• Basic knowledge of AI
• Power BI

- Postgre SQL
- DBT

📌 Data Engineer Lead (Noida)
🏢 IRIS SOFTWARE
📍 Noida