Description
Thread is seeking a motivated Data Analyst Intern to join our growing Data & Analytics team. This role is a unique opportunity to gain hands-on experience working across various functions of a modern data organization, including data ingestion, quality control (QC), automation, and data governance.
The ideal candidate is detail-oriented and eager to learn the foundational practices that support trusted, well-documented, and high-quality data systems. You will work closely with data engineers and product leaders to help ensure the integrity, accessibility, and usability of our data assets.
• Assist in the ingestion and validation of new data sources from internal and external systems.
• Support data quality control (QC) processes by identifying anomalies, inconsistencies, and missing data, and working with engineers to address them.
• Help develop and maintain data documentation, including data dictionaries, source mappings, and lineage records.
• Collaborate with the Data Product Lead and COO to track and improve data governance practices, including naming conventions, metadata standards, and access policies.
• Participate in data testing, reconciliation, and profiling activities.
• Support ad hoc data investigations, reporting, and analysis as needed by the data team.
• Contribute to the development and improvement of internal workflows and documentation.
Requirements
Required:• Currently pursuing a degree in Data Science, Computer Science, Information Systems, Statistics, or a related field.• Basic knowledge of SQL and comfort working with data tables.• Strong attention to detail and ability to follow structured processes.• Excellent written and verbal communication skills.• Eagerness to learn and collaborate with cross-functional teams.
Nice to Have:• Exposure to Python or other scripting languages.• Familiarity with data cataloging tools or governance platforms.• Experience using BI tools (e.g., Looker, Power BI, Tableau).• Understanding of data lifecycle, data pipelines, or cloud-based data platforms (e.g., Snowflake, BigQuery, or AWS/GCP).
• Exposure to real-world data engineering and analytics processes.• Practical experience in data governance and documentation standards.• Opportunities to work cross-functionally and understand how data supports business decisions.• Mentorship from experienced data professionals and leadership.
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