Program for Poshmark Data Analytics Internships : Candidates are being sought for the position of Data Analyst Intern at Poshmark’s Chennai branch. The following contains all of the information regarding the Poshmark Data Analytics internship program.
| Company Name | Poshmark |
| Role | Data Analyst Intern |
| Location | Chennai, Tamil Nadu |
| Salary | Upto 40,000rs/Month |
| Internship Duration | 6 months |
Jobs Descriptions
- Job Position: Data Analyst Intern
- Job Location: Chennai
- Salary Package:
- Full/Part Time: Full Time
- Education Level: Only 2025 pass out can apply
Qualifications & Educations
- strong knowledge of ETL procedures, data pipelines, and data warehousing.
- ability to query data using SQL and a desire to learn about other database systems (relational, columnar, and NoSQL like MongoDB and Redshift).
- It is advantageous to have prior experience using BI tools such as Looker, Tableau, or others.
- Basic to advanced knowledge of Python, with an emphasis on data task scripting.
- enthusiasm for managing data governance, dealing with big datasets, data architecture, and intricate workflows.
- It’s nice to have DBT experience.
- It is also advantageous to be familiar with AWS services (IAM, EC2, EMR).
Soft Skills for jobs
Thinking analytically and having a problem-solving mindset
enthusiastic about data and creating things that are based on data.
familiarity with using Microsoft PowerPoint or a comparable program to create presentations
outstanding interpersonal communication abilities, both in writing and speaking.
Skills Required Responsibilities
- Develop data solutions for new product and feature releases in a proactive manner with stakeholders, paying close attention to streamlining and resolving any subtleties or problems in the data pipeline.
- Work autonomously, show originality, and produce outcomes fast while keeping a cooperative, team-oriented mindset.
- Apply best practices discovered by other teams, work well with cross-functional teams, and constantly aim for high-caliber outputs.
- To guarantee clarity and accessibility for future reference and teamwork, create and maintain thorough documentation.
- To guarantee data integrity and quality, conduct comprehensive quality assurance (QA). Report any issues in accordance with regular procedures, and work with the appropriate data teams to find solutions.
