
Data Engineer Position
2 days ago
About the Role
">We are seeking a talented and experienced Data Engineer to join our expanding Data & Analytics team. As a key member of this team, you will play a pivotal role in the development of high-quality data lakehouse products and solutions.
Key Responsibilities
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- Design, build, and maintain scalable data pipelines and systems.
- Collaborate with cross-functional teams to understand data requirements and develop appropriate solutions.
- Implement and automate ETL processes to extract, transform, and load data from various sources.
- Develop real-time data pipelines and applications using serverless and managed AWS services such as Kafka, Lambda, Kinesis, API Gateway, REST Api, etc.
- Standardize and cleanse data for AI, Data Science, and Analytics use cases to support business needs.
- Create and optimize databases and data models for efficiency and performance.
- Ensure data quality and integrity by performing data validations and implementing quality checks.
- Develop and maintain documentation related to data infrastructure and processes.
- Troubleshoot and resolve data-related issues.
Required Skills and Qualifications
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- 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.
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