Description

Key Skills: AWS, AWS Cloud, Databricks, Python, Data Engineer, Data Engineering, Spark

Roles and Responsibilities:

• Design and implement scalable cloud-based data solutions using AWS and Databricks to support enterprise analytics and reporting.
• Lead technical direction and roadmap execution for data engineering initiatives, ensuring alignment with enterprise architecture and standards.
• Build and maintain production data pipelines with strong data governance, quality controls, and minimal manual intervention.
• Use DevOps tooling (e.g., GitHub, Jenkins, Terraform, Liquibase) to streamline delivery and operational processes.
• Provide day-to-day leadership for a small team of engineers, including code reviews, merge request oversight, and coaching to ensure high-quality delivery.

Skills Required:

• 15 to 20 years of experience in application program development and data engineering.
• AWS (including core services such as S3, EC2, RDS, VPC, IAM) and hands-on AWS service experience.
• Databricks for building and operating data engineering workloads.
• Python for modular, maintainable data engineering code.
• Data engineering fundamentals for designing scalable data assets and pipelines.

Good to Have:

• Spark for large-scale data processing and real-time/near-real-time analytics frameworks.

Education: Bachelor's degree in Engineering, Computer Science, or related discipline

Key Skills

Education

Any Graduate