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Data Engineer - Data Lakehouse

ZILO is focused on transforming global transfer agency by providing a single global solution that replaces legacy technology and systems. Our mission is to create sustainable value for firms and the customers they serve, all while putting people first. With a design-driven approach and a commitment to innovation, our team of experts has unified the full breadth of global transfer agency into a single, streamlined solution.

At ZILO, we value collaboration, innovation, and continuous improvement. Our team of experienced professionals is dedicated to achieving our goal of being the market-leading solution in global transfer agency. If you are a motivated individual with a passion for technology and a desire to make a real impact in the financial services industry, we would love to hear from you.

About this role

We are seeking a skilled Data Engineer – Data Lakehouse to join our team. The ideal candidate should be experienced in designing and building data pipelines, performing ETL operations, and managing databases. The candidate will also need to have knowledge and experience in using AWS services for data processing, storage, and analysis.

Responsibilities

  • Design, build and maintain efficient and scalable data pipelines to support data processing and analysis.
  • Develop and implement ETL processes to ensure data quality and integrity.
  • Manage and optimize databases, including designing schema and indexing strategies,data partitioning and data archival.
  • Work closely with data scientists and business analysts to understand datarequirements and translate them into technical solutions.
  • Collaborate with DevOps and IT teams to deploy, monitor and troubleshoot datasystems.
  • Develop and maintain documentation on data infrastructure and processes.
  • Stay current with the latest data engineering technologies, tools and practices.

Qualifications

  • Bachelor's degree in computer science, engineering or related field.
  • Minimum of 3 years of experience in data engineering roles.
  • Strong proficiency in SQL, ETL processes and database management systems (e.g.,MySQL, PostgreSQL, MongoDB).
  • Hands-on experience with AWS services for data processing, storage and analysis(e.g., S3, Redshift, EMR, Glue).
  • Familiarity with programming languages such as Python or Java.
  • Understanding of data warehousing concepts and data modeling techniques.
  • Experience working with big data technologies (e.g., Hadoop, Spark) is an advantage.
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration skills

- 23 annual holidays (start and fix at 23 days)

- 15 public holidays

- Provident fund up to 12%

- Health Insurance (including immediate family)

- etc

What You Should Know About Data Engineer - Data Lakehouse, ZILO

Join ZILO as a Data Engineer - Data Lakehouse and be at the forefront of transforming the global transfer agency landscape. At ZILO, we pride ourselves on developing innovative solutions that replace outdated technology, and we’re passionate about creating sustainable value for our clients and their customers. In this role, you’ll play a critical part in building and maintaining efficient data pipelines designed to support robust data processing and analysis. If you bring experience in ETL processes and database management, along with a strong understanding of AWS services like S3 and Redshift, we’d love to see what you can bring to our dynamic team. Your responsibilities will include collaborating with data scientists to translate business requirements into technical solutions, optimizing databases, and ensuring the integrity of the data we manage. We are committed to fostering a collaborative work environment where innovation thrives. With your strong problem-solving skills and ability to communicate effectively, you will ensure that our data systems run smoothly and efficiently. At ZILO, we believe in a people-first approach, and that extends to how we support our employees. You can expect generous annual leave, health insurance, and a focus on continuous professional growth. If you’re motivated to make a significant impact in the financial services sector and you’re ready to bring your expertise to our forward-thinking company, we can’t wait to meet you!

Frequently Asked Questions (FAQs) for Data Engineer - Data Lakehouse Role at ZILO
What are the responsibilities of a Data Engineer - Data Lakehouse at ZILO?

As a Data Engineer - Data Lakehouse at ZILO, you’ll be responsible for designing, building, and maintaining data pipelines, developing ETL processes, managing and optimizing databases, collaborating with team members on data requirements, and documenting data infrastructure and processes to ensure seamless operations.

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What qualifications are needed for the Data Engineer - Data Lakehouse position at ZILO?

To be successful as a Data Engineer - Data Lakehouse at ZILO, you should have a Bachelor's degree in computer science or a related field, at least 3 years of experience in data engineering, strong SQL and ETL skills, familiarity with AWS services, and an understanding of programming languages like Python or Java.

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How does ZILO support professional growth for Data Engineers?

At ZILO, we are committed to continuous improvement and professional growth. Data Engineers have opportunities for training and development in the latest technologies and practices. We prioritize collaboration and innovation, allowing team members to enhance their skill sets while contributing to impactful projects.

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What programming languages are preferred for the Data Engineer - Data Lakehouse role at ZILO?

For the Data Engineer - Data Lakehouse role at ZILO, familiarity with programming languages such as Python or Java is important. These languages are essential for developing data processing scripts and automating tasks within your data pipelines.

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What benefits does ZILO offer to Data Engineers in this role?

ZILO values its employees and offers a comprehensive benefits package which includes 23 annual holidays, 15 public holidays, up to 12% provident fund, and health insurance coverage for you and your immediate family, aiming to foster a healthy work-life balance.

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Common Interview Questions for Data Engineer - Data Lakehouse
Can you explain the role of ETL in data engineering?

ETL, or Extract, Transform, Load, is a crucial process in data engineering that involves extracting data from various sources, transforming it into a suitable format, and loading it into storage systems. Discuss how ETL enhances data quality and prepares datasets for analysis.

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What experience do you have with AWS services relevant to data engineering?

In answering this question, be specific about the AWS services you’ve used, such as Amazon S3 for storage, Redshift for data warehousing, and Glue for ETL. Provide examples of how you implemented these services in past projects.

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How do you ensure data integrity while building data pipelines?

To ensure data integrity, you can discuss the importance of validation checks during ETL processes, consistent schema design, and data cleaning techniques. Mention how you have employed these practices in your previous roles.

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What strategies do you use for database optimization?

Talk about strategies such as indexing, partitioning tables, and normalizing data to reduce redundancy. Share specific experiences where you implemented these optimizations to improve database performance.

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Describe a challenging data problem you faced and how you solved it.

Provide a specific example demonstrating your problem-solving skills. Discuss the context of the challenge, the steps you took to address it, and the positive outcome that resulted from your solution.

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How do you stay updated on the latest data engineering technologies?

Describe your approach to continuous learning, such as following industry blogs, participating in online courses, or attending conferences. Mention how up-to-date knowledge has helped you apply new techniques in your work.

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How would you communicate technical information to a non-technical audience?

Emphasize your ability to simplify complex concepts using analogies, visual aids, or dashboards. Give examples of how you've successfully communicated data-related topics to stakeholders without a technical background.

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What data modeling techniques are you familiar with?

Discuss your knowledge of various data modeling techniques, such as star schema and snowflake schema. Explain how you have applied these techniques in designing efficient data architecture in previous projects.

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What tools do you use for monitoring and troubleshooting data systems?

Identify the tools you are familiar with, such as AWS CloudWatch or other monitoring software. Explain how you use these tools to proactively monitor data systems and address issues before they impact performance.

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What are the key differences between a data lake and a data warehouse?

Explain the differences between data lakes and data warehouses, focusing on aspects such as data structure, storage type, and use cases. Illustrate your understanding with examples of when to use each in business contexts.

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Zillow Group houses a portfolio of the largest and most vibrant real estate and home-related brands on the Web and mobile.

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Full-time, remote
DATE POSTED
December 26, 2024

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