About the Job:

The Senior Data Engineer position offers an exciting opportunity to work in a dynamic environment where you will be responsible for designing, developing, and maintaining scalable ETL pipelines. As a key member of the team, you will collaborate with data scientists, analysts, and engineers to ensure data accuracy and integrity while staying updated with the latest technologies in data engineering.

Roles & Responsibilities:

• Design, develop, and maintain scalable ETL pipelines for data ingestion and transformation.
• Optimize data warehouse architecture on AWS for performance and cost-effectiveness.
• Implement data models to support business requirements and analytical needs.
• Write clean and efficient code in Python and Spark for data processing and automation.
• Ensure data quality through monitoring systems and data accuracy checks.
• Collaborate with cross-functional teams to provide necessary data infrastructure and tools.
• Troubleshoot and resolve data-related issues promptly.
• Stay updated with the latest trends in data engineering and cloud computing.
• Participate in code reviews and contribute to engineering standards improvement.
• Mentor junior data engineers and contribute to project planning and execution.

Required Skills & Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 5-10 years of experience in data engineering roles.
• Strong understanding of data warehousing concepts and dimensional modeling.
• Experience with ETL/ELT pipelines using Apache Spark, AWS Glue, or similar tools.
• Proficiency in Python, SQL, and data manipulation libraries.
• Hands-on experience with big data technologies like Spark and Hadoop.
• Working knowledge of AWS services including Redshift, Glue, S3, EC2, etc.
• Experience with SQL, relational databases, and NoSQL databases.
• Strong problem-solving and analytical skills with excellent communication abilities.
• Ability to work independently and collaboratively in a fast-paced environment.