Data Engineer

As a Data Engineer at OneMagnify, you will leverage advanced data tools and capabilities to support clients' analytics needs. Your responsibilities include conducting in-depth data analysis to improve data quality, developing comprehensive data product solutions, and manipulating large datasets using SQL to identify patterns. Additionally, you'll collaborate with data owners to enhance data governance and ensure compliance with privacy standards. Overall, the role is pivotal in advancing our Data & Analytics Road Map.

To succeed as a Data Engineer at OneMagnify, you should hold a university degree in Computer Science, Mathematics, Engineering, or a related field. You also need at least 2 years of relevant experience in gathering requirements and creating technical specifications for data solutions. Proficiency in advanced SQL scripting is essential, and familiarity with Python and platforms like AWS and Snowflake will give you an edge. Understanding data governance and metadata management is a plus.

A strong background in SQL scripting is crucial for the Data Engineer role at OneMagnify. In addition to this, experience with the AWS platform and its analytical tools such as S3, Redshift, and Glue will enhance your effectiveness. Knowledge of data governance principles, as well as familiarity with tools like Monte Carlo and Atlan, will also be beneficial. Being able to analyze and interpret complex data requirements is key to driving successful data solutions.

OneMagnify is committed to employee development, offering numerous opportunities for growth, including training programs, mentorships, and a supportive work environment. As a Data Engineer, you'll be encouraged to continually enhance your skills, whether through hands-on projects or formal education. Additionally, being part of a recognized top workplace emphasizes our dedication to creating a culture that nurtures talent and inspires excellence.

As a Data Engineer at OneMagnify, you will work on diverse projects that involve leveraging data to drive marketing strategies and enhance brand performance. This includes conducting discovery analyses, developing data models, and ensuring data quality and governance, all aimed at optimizing customer insights. You will collaborate with various teams, delivering solutions that significantly influence our clients' business outcomes.

In answering this question, detail specific projects where your SQL skills were key to data manipulation or analysis. Describe how you’ve used SQL for tasks like querying large datasets, optimizing performance, or generating reports. Incorporate examples of challenges faced and how your solutions impacted the project positively.

Focus on a specific situation where you identified a data issue, such as inconsistencies or quality problems. Explain your systematic approach to troubleshooting, including the tools used (e.g., SQL for data profiling) and the outcome. Highlight the problem-solving techniques you employed to uncover the root cause.

Discuss strategies you've implemented in previous roles to maintain data quality, such as creating checks and balances, using profiling tools, or establishing governance frameworks. Illustrate how you collaborate with data stewards or stakeholders to enhance data integrity and quality standards.

Highlight your familiarity with AWS services like S3 and Redshift. Give examples of how you utilized these tools in past projects or how they contributed to analytics workflows. If applicable, include knowledge of Snowflake and any relevant projects you’ve managed using these platforms.

Share the significance of data governance and how it affects data operations. Discuss standards and best practices you've adhered to in maintaining metadata management, security, and compliance. Emphasize how your understanding ensures responsible data usage while contributing to business success.

Illustrate your collaborative work style by describing past experiences working with teams such as data scientists, marketers, or product owners. Share examples of how you communicated data findings effectively and coordinated efforts to achieve project goals, emphasizing teamwork and positive outcomes.

Talk about your process for documenting requirements, specifications, and methodologies. Explain how you ensure clarity and organization in your documentation, using templates or tools when necessary, so that teams can reference them easily. Highlight the importance of this documentation for successful project execution.

Share specific instances where you utilized Python for data manipulation, automation, or analysis. Link your Python experience to key results, such as streamlining processes or improving insights derived from data. Mention any libraries or frameworks relevant to your role.

Address challenges such as data management issues, evolving technologies, or stakeholder communication. Discuss your strategies for overcoming these challenges, such as continuous learning, keeping abreast of industry trends, or leveraging team resources effectively. Highlight resilience and adaptability.

Convey your enthusiasm for being part of OneMagnify’s innovative culture. Relate your skills and experience to the company's mission of blending technology with marketing analytics. Discuss how the role aligns with your career goals and your desire to contribute to transformative data solutions.