Data Analyst

As a Data Analyst at YUPRO Placement, your key responsibilities include maintaining documentation for data assets, resolving privacy issues, managing data quality checks, ensuring the availability of data tables, and deprecating stale data. You'll work closely with the Data Engineering team to support Global Operations through these tasks.

To qualify for the Data Analyst role at YUPRO Placement, candidates should have a minimum of 2 years of experience in developing ETL pipelines, strong SQL skills, and familiarity with data visualization tools such as Tableau or Power BI. Knowledge of data governance best practices and experience with platforms like AWS or GCP are also beneficial.

Data quality checks are crucial for a Data Analyst at YUPRO Placement as they ensure the integrity of the data being used for decision-making. Implementing these checks helps in identifying errors early and maintaining a high standard of data quality, which is essential for supporting Global Operations effectively.

Data Analysts at YUPRO Placement will primarily work with SQL databases, data visualization tools such as Tableau or Power BI, and may also engage with Meta's data infrastructure tools like Hive, Presto, and Spark, ensuring robust data management and analysis.

The work environment at YUPRO Placement for Data Analysts is collaborative and inclusive, focusing on both independent and teamwork. The office is located in Washington, DC, and emphasizes a supportive culture where diverse skills and perspectives are valued, making it a great place for personal and professional growth.

When answering this question, highlight specific ETL projects you have worked on, detailing the tools and technologies you used, your role in the process, and how your contributions led to successful outcomes.

Discuss your strategies for implementing data quality checks, such as data validation, anomaly detection, and regular audits. Provide examples of how you have identified and resolved data issues in previous projects.

Use the STAR method (Situation, Task, Action, Result) to clearly describe the problem, your approach to tackling it, the actions you took, and the positive results that followed. This structure helps convey your analytical and problem-solving skills effectively.

Share specific SQL functions that you regularly use, such as JOINs, GROUP BY, and aggregate functions. It’s also beneficial to mention scenarios where these functions helped you extract meaningful insights.

Talk about your approach to task management, whether it's through prioritizing based on deadlines, impact, or stakeholder needs. Highlight any tools or methods you use to keep track of your responsibilities.

Mention specific projects where you used tools like Tableau or Power BI, explaining how they helped communicate complex data insights to stakeholders and what impact those visualizations had.

Explain your process for investigating data discrepancies, such as checking source data, running consistency checks, collaborating with team members, and how you document the resolutions.

Discuss the importance of tailoring your communication style based on your audience. Share examples where you broke down technical concepts into layman's terms or used visual aids to clarify your points.

Outline your experience with cloud environments like AWS, GCP, or Azure and discuss projects where you utilized these platforms. Highlight any specific tools or services you've worked with and how they enhanced your data processes.

Reflect on attributes that contribute to success in this role, such as attention to detail, critical thinking, and a proactive attitude. Share instances where these qualities have enabled you to excel in previous positions.