Data Quality Engineer

Job Description

A streaming client is in need of hiring a unique candidate who is a Data Quality Engineer who not only understands data and has the technical background, but also someone who has a 'quality engineering and testing mindset', who is passionate about testing. This role is crucial for a company-wide integration initiative that affects business, technology, and content integrations of this company's streaming services into it's broader streaming ecosystem. It involves:• Merging platforms• Consolidating tech stacks and data pipelines• Unifying content and sports rights• Migrating users and subscriptions at massive scale• Reorganizing teams and governance

This is a technical role where you are required write clean/strong Python code, but also have strong QA/testing skills (i.e. create test plans and test cases, and ensure extensive coverage). In addition, you may also be responsible for helping build the automation process/framework(s) for data validation for all streaming-related data for subscriber info (etc.), from this client's multiple streaming platforms. You will be required to attend team/scrum meetings and sprint stand ups and planning sessions.

You will use automation while doing ETL validations (i.e. the ETL is already built by a different team), so you will be responsible for validating the ETL and adhere to standards. In addition, this team is really looking for a candidate who is passionate about learning, is collaborative, and has excellent communication. This is NOT a Python programming role, it is strictly a QA testing role within data engineering/quality.

Required Skills & Experience

• Must be able to work from 2-10pm IST, but also be expected to log on/work until 12am IST to be on stand up meetings with the team-5-10 years of experience as a Sr. Data Quality Engineer/Tester, who is focused on/passionate about testing data/ETL pipelines, etc.-Strong Python programming/coding skills AND strong QA/testing skills-Strong background in SQL, and conducting/building strong test cases and plans-ETL testing/validation experience-Understanding of business logic validations-Big data experience (Hadoop, Spark, Hive - any is fine)-Experience working in a Scrum environmentAWS experience-Databricks experience-Snowflake experience