High-Quality Data Product Engineer

About Us

1. Data Engineers are responsible for designing, building, and maintaining scalable data pipelines and systems.
2. They collaborate with cross-functional teams to understand data requirements and develop appropriate solutions.
3. Implement and automate ETL processes to extract, transform, and load data from various sources, building Data Lakehouse solutions.
4. Develop real-time data pipelines and applications using serverless and managed AWS services such as Kafka, Lambda, Kinesis, API Gateway, REST Api, etc.
5. Develop scalable ETL pipelines for structured, semi-structured, and unstructured data, including both batch and streaming processes.
6. Standardize and cleanse data for AI, Data Science, and Analytics use cases to support business needs.
7. Create and optimize databases and data models for efficiency and performance.
8. Ensure data quality and integrity by performing data validations and implementing quality checks.
9. Develop and maintain documentation related to data infrastructure and processes.
10. Troubleshoot and resolve data-related issues.
11. Stay up to date with the latest trends and technologies in data engineering and data management.

We're Seeking a Talent

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Possess a deep passion for data and a demonstrated ability to create high-quality data products.
• 4+ years of experience working with customer-centric data on a big data scale, preferably in a banking, online, or e-commerce context.
• 4+ years of hands-on experience building production data pipelines and working with structured, semi-structured, and unstructured data.
• 3+ years of experience in engineering data solutions within both cloud and hybrid infrastructures, with strong expertise in AWS Cloud.
• 2+ years of experience with one or more programming languages, especially Python.
• 2+ years of experience with data integration/ETL technologies such as Python, Spark/PySpark, Kafka/Kinesis/EMR, Lambda, API Gateway, REST API, AWS Glue, etc.
• Proficient in database technologies like AWS S3, MongoDB, DynamoDB, AWS Redshift, Glacier, and other SQL and NoSQL databases.
• Experienced with CI/CD pipelines and tools such as Jenkins, GitLab CI, or Azure DevOps.
• Experience with modern real-time data pipelines (e.g., serverless framework, Lambda, Kinesis, etc.).
• Experience designing ETL/ELT process flows for Data Lakehouse implementation.
• Experience in AWS data ecosystem and various other cloud services.
• Experienced in different APIs and API integration, along with microservice architecture.
• Experience integrating customer contact center data with data Lakehouse is a plus.
• Strong analytical, logical, problem-solving and numerical skills.
• A self-starter and creative thinker who collaborates well and communicates confidently.
• Effective in communicating with both technical and non-technical audiences.
• Proven ability to take initiative and proactively learn new technologies.
• Demonstrates a solid work ethic and provides timely, high-quality support.
• Embraces a mindset of Continuous Improvement.

Why Choose Us

Our global network of industry experts and mentors helps shape your growth and future. We believe in delivering client value through our work. We build products that are not good or great, but outstanding.

You deliver - we will make your stay and journey with us worthwhile.

We are an equal opportunity employer, and we value diversity. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other legally protected status.