QA Engineer Intern

Abacus Insights

37d

About The Position

Our TechOps team is excited to bring on a Data QA Engineer Intern to support a critical feature delivery team. This role is an excellent opportunity for someone looking to gain hands-on experience in data quality, testing, and modern data engineering practices. As part of the Connector Factory team, you will help validate and support data pipelines that ingest, transform, and process diverse data sources. You’ll gain exposure to large-scale batch and streaming systems, as well as key AWS technologies such as Lambda, EMR (Hadoop/Spark), and EKS (Kubernetes). This internship will give you broad visibility into our platform and a chance to contribute to the ongoing evolution of our data architecture. You’ll learn industry best practices, collaborate with experienced engineers, and play a meaningful role in ensuring the accuracy and reliability of our data products as the organization continues to grow rapidly.

Requirements

Interest in learning about healthcare data and foundational ETL concepts.
Currently pursuing or recently completed a Master’s degree in a quantitative or technical field (e.g., Computer Science, Data Science, Statistics, Engineering).
Basic understanding of data management principles and data storage concepts.
Exposure to data analysis through coursework or projects, with a willingness to work with large datasets.
Familiarity with SQL and a desire to develop stronger querying skills.
Interest in ETL testing or big data validation, even if only through academic or personal projects.
Some experience with Python scripting from classes or hands-on exercises.
Familiarity with PySpark or Databricks through coursework, labs, or online learning is beneficial.
Basic understanding of cloud platforms AWS, DataBricks is a plus.

Nice To Haves

Exposure to healthcare payer data concepts
Experience with other Cloud Data Warehouses (Big Query, Snowflake)
Hands on experience of API testing
ETL testing automation experience

Responsibilities

Assist in estimating effort for QA tasks under the guidance of senior team members.
Review requirement and mapping documents to help identify potential gaps or clarifications needed.
Support the creation of test scenarios and contribute to writing basic ETL test cases.
Learn to interpret various input file layouts and participate in parser validation activities.
Write simple Source and Target SQL queries to support data validation efforts.
Contribute to automating data validation workflows using tools such as PySpark or Databricks.
Help prepare test data, including generating synthetic datasets that mimic real-world scenarios.
Assist in writing SQL queries to validate User Acceptance Criteria.
Provide support during User Acceptance Testing (UAT) cycles.
Participate in daily Agile ceremonies and follow Agile practices as part of the delivery team.
Document QA activities using test management tools and Jira.
Collaborate with onsite and offshore team members to support day-to-day QA tasks.