DATA ENGINEER (SQL & AWS)

Start Date
Urgent /ASAP
Experience Level
8-12 yrs
Job Summary
We are seeking a highly skilled Data Engineer with deep expertise in SQL (including stored procedures) and AWS-based data engineering solutions. You will be responsible for designing, building, and optimizing scalable data pipelines and systems that enable analytics, reporting, and data-driven decision-making across the organization.

Key Responsibilities

• Develop, and optimize complex SQL queries and stored procedures for high-performance data processing and transformation.
• Build and maintain scalable ETL/ELT pipelines on AWS using services such as Glue, Lambda, S3, Athena, Redshift, and Step Functions.
• Implement and maintain data integration solutions from various data sources into a centralized data lake or data warehouse.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver reliable solutions.
• Monitor and troubleshoot data pipelines to ensure data accuracy, timeliness, and reliability.
• Apply data governance and security best practices in all development work.

Skills Required

• Expert-level proficiency in SQL, including performance tuning, writing complex joins, and stored procedures in databases.
• Experience with AWS Data Engineering tools

AWS Glue
Amazon Redshift
AWS Lambda
Amazon S3
Athena
Step Functions
Experience with data modeling, ETL orchestration, and data pipeline development in AWS.
Familiarity with version control systems (e.g., Git) and CI/CD for data workflows.

Airflow

• Experience with Python and PySpark

• Develop, and optimize complex SQL queries and stored procedures for high-performance data processing and transformation.
• Build and maintain scalable ETL/ELT pipelines on AWS using services such as Glue, Lambda, S3, Athena, Redshift, and Step Functions.
• Implement and maintain data integration solutions from various data sources into a centralized data lake or data warehouse.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver reliable solutions.
• Monitor and troubleshoot data pipelines to ensure data accuracy, timeliness, and reliability.
• Apply data governance and security best practices in all development work