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Data Engineer

1. Data Pipeline

  • Develop and optimize ETL/ELT pipelines using modern data tools and frameworks
  • Write efficient code in Python and SQL for data transformation and processing
  • Implement data validation and testing frameworks
  • Create automated workflows for data processing and monitoring
  • Troubleshoot and resolve data pipeline issues

2. Data Warehousing

  • Design and maintain enterprise data warehouse architecture
  • Implement dimensional modeling and data mart solutions
  • Optimize query performance and data access patterns
  • Develop data documentation and lineage tracking
  • Create and maintain data schemas and models
  • Implement data governance and quality control mechanisms

  • 5+ years of experience in data engineering.
  • Bachelor's degree or higher in Computer Science, Data Engineering, or a related field.
  • Advanced SQL and Python programming skills, including optimization and performance tuning.
  • Strong proficiency in cloud platforms (GCP, AliCloud, AWS).
  • Expertise in big data technologies (Spark, Flink, Presto, StarRocks, Data Lake, Airflow).
  • Solid understanding of data warehousing concepts and best practices.
  • Experience with BI tools (Tableau, Looker, Datawind).
  • Knowledge of data quality frameworks and tools.
  • Strong problem-solving, analytical, and communication skills.
  • Ability to work independently and collaboratively in a fast-paced environment.
  • Experience in the financial services or fintech industry, particularly within the crypto/blockchain space, is a strong plus.

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What You Should Know About Data Engineer, OSL

Are you ready to take your data engineering skills to the next level? Join us as a Data Engineer at our dynamic company where your expertise will drive our data architecture initiatives! In this role, you will develop and optimize ETL/ELT pipelines using modern data tools, writing efficient Python and SQL code for seamless data transformation and processing. Your mission includes implementing robust data validation and testing frameworks, creating automated workflows for smooth data processing, and troubleshooting any pipeline issues that arise. You'll also design and maintain our enterprise data warehouse architecture, work on dimensional modeling, and optimize query performance to ensure rapid data access. With a solid background of 5+ years in data engineering, and a Bachelor's degree or higher in Computer Science or related fields, you will shine with your advanced skills in SQL and Python, especially in optimization and performance tuning. You’ll have the opportunity to work with cloud platforms such as GCP, AWS, or AliCloud, and you'll get hands-on experience with big data technologies like Spark, Flink, and Airflow. If you have a passion for the fintech industry, particularly in the crypto/blockchain space, your knowledge will definitely set you apart. Get ready to collaborate with a talented team in a fast-paced environment where problem-solving and analytical skills are key to your success!

Frequently Asked Questions (FAQs) for Data Engineer Role at OSL
What are the main responsibilities of a Data Engineer at our company?

As a Data Engineer at our company, your main responsibilities include developing and optimizing ETL/ELT pipelines, writing efficient Python and SQL code for data transformation, implementing data validation processes, designing and maintaining enterprise data warehouse architecture, and ensuring data quality and governance.

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What qualifications do I need to become a Data Engineer at our company?

To become a Data Engineer at our company, you should have at least 5 years of experience in data engineering, a Bachelor's degree or higher in Computer Science or a related field, and advanced skills in SQL and Python. Proficiency in cloud platforms and big data technologies is also essential.

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What technologies should a Data Engineer be familiar with at our company?

A Data Engineer at our company should be familiar with various technologies including cloud platforms (GCP, AWS, AliCloud), big data tools (Spark, Flink), and data warehousing concepts. Knowledge of BI tools like Tableau or Looker will also be beneficial.

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Is experience in fintech necessary for the Data Engineer role?

While not mandatory, experience in the fintech industry, especially within the crypto/blockchain space, is a strong plus for a Data Engineer role at our company. It can provide valuable insights into the data challenges specific to the financial services sector.

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What sort of work environment can I expect as a Data Engineer at your company?

You can expect a collaborative and fast-paced work environment as a Data Engineer at our company. We value both independent work and teamwork, with a strong emphasis on problem-solving, communication, and analytical skills.

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Common Interview Questions for Data Engineer
What experience do you have with ETL/ELT pipelines?

In answering this question, focus on specific projects where you've developed ETL/ELT pipelines. Discuss the tools you used, challenges you faced, and how you optimized those pipelines for efficiency.

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How do you ensure data quality in your work as a Data Engineer?

Explain your strategies for data quality assurance, such as implementing data validation frameworks, utilizing testing, and tracking data lineage. Providing examples from your previous roles will strengthen your response.

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Can you describe your experience with cloud platforms like AWS or GCP?

Share specific instances of how you've leveraged cloud platforms to store, process, or analyze data. Discuss any certifications you have and particular projects where cloud technology played a pivotal role.

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What role do you believe dimensional modeling plays in data warehousing?

Discuss the significance of dimensional modeling in making data warehouse queries more efficient and user-friendly. Provide examples of how you've implemented or supported dimensional modeling in your previous work.

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How do you approach performance tuning in SQL?

Talk about your methods for analyzing and optimizing SQL queries. Mention any performance tuning techniques or tools you use that have helped you improve query response times.

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Describe a challenging problem you've solved in your data engineering career.

Choose a specific challenge that showcases your analytical skills and problem-solving abilities. Detail the steps you took to resolve the issue and the outcome.

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What big data technologies have you worked with?

Mention your experience with big data technologies such as Spark or Flink. Describe how you utilized these tools in projects to handle large datasets effectively.

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How do you stay updated with the latest trends in data engineering?

Discuss the resources you use to stay current, such as blogs, online courses, webinars, and networking with other data professionals. Highlight any recent new skills or technologies you've adopted.

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What BI tools are you familiar with and how have you used them?

State your experience with BI tools like Tableau or Looker, and discuss how you've applied them to visualize or analyze data for stakeholders in your previous roles.

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How would you collaborate with data scientists or analysts?

Explain your approach to collaboration, focusing on communication skills, understanding their needs regarding data access, and how you can facilitate their work through effective data engineering practices.

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OSL is Asia's most comprehensive digital asset platform, providing Software-as-a-Service (SaaS), brokerage, exchange and custody services for institutional clients and professional investors. The company offers OTC trading services, access to la...

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Full-time, remote
DATE POSTED
January 7, 2025

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