Software Engineer (Data)

Job Overview:

We are looking for a skilled Software Engineer to join our Data Engineering team. In this role, you will be responsible for designing, building, and maintaining backend APIs to support our data and ETL (Extract, Transform, Load) processes. You will work closely with cross-functional teams to ensure the seamless integration and accessibility of data across the organization.

Key Responsibilities:

• Design, develop, and maintain backend APIs for data processing and ETL workflows.
• Collaborate with data scientists, analysts, and other engineering teams to understand data requirements and deliver solutions.
• Implement scalable and efficient data pipelines using Python and SQL.
• Utilize Java for high-performance data processing tasks.
• Deploy, monitor, and maintain data infrastructure on Google Cloud Platform (GCP).
• Ensure data integrity, quality, and security through best practices and robust testing.
• Optimize and improve existing data systems for performance and scalability.
• Troubleshoot and resolve issues in a timely manner.
• Document technical solutions and contribute to knowledge sharing within the team.

Required Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience.
• 6+ years of experience in software engineering, with a focus on data and backend development.
• Proficiency in Python, Java, and SQL.
• Experience with Google Cloud Platform (GCP) and its services (e.g., BigQuery, Dataflow, Pub/Sub).
• Strong understanding of data modeling, ETL processes, and data warehousing concepts.
• Experience with RESTful API design and development.
• Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.

Preferred Qualifications:

• Experience with other cloud platforms (e.g., AWS, Azure).
• Knowledge of containerization and orchestration (e.g., Docker, Kubernetes).
• Experience with big data technologies (e.g., Hadoop, Spark).
• Familiarity with machine learning and data analytics.