Key Responsibilities:

Design, develop, and maintain ETL pipelines for structured and semi-structured data

Build data models and optimize performance on Snowflake data warehouse

Work with AWS services (e.g., S3, Lambda, Glue, Redshift, EC2) to handle large-scale data workflows

Write efficient, reusable, and testable Python code for data manipulation and pipeline automation

Perform data validation and ensure data quality across ingestion and transformation layers

Collaborate with analysts, data scientists, and business teams to deliver reliable datasets

Monitor pipeline performance and troubleshoot issues proactively

Required Skills:

5+ years of experience in data engineering or a similar role

Strong experience with ETL tools/processes

Proficient in Snowflake (data modeling, performance tuning, SQL scripting)

Hands-on with AWS cloud ecosystem, especially S3, Glue, Lambda, Redshift

Strong programming skills in Python

Familiarity with orchestration tools like Airflow or AWS Step Functions

Experience working with large datasets, batch and streaming data pipelines

Preferred Qualifications:

Experience with DevOps/DataOps practices (CI/CD for data)

Knowledge of data governance, security, and compliance best practices

Experience in agile development environments

Education:

Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field.