What are the responsibilities and job description for the ETL & Data Quality Engineer - Major Entertainment Company (No C2C or H1B) position at TechLink Resources?
Job Details
ETL & Data Quality Engineer
Job Description
We are seeking a highly skilled ETL & Data Quality Engineer to test and validate ETL logic and data pipelines, ensuring the quality and reliability of data in production. This role will play a critical part in delivering high-quality operational data to support subscriber and commerce operations.
As part of the team, you will partner closely with Data Analysts, Product, and Engineering teams to understand transactional system behaviors and business use cases, translating technical specifications into robust testing requirements. You will also help build automated and reusable test frameworks to enhance quality assurance and development velocity.
Key Responsibilities
Test and validate ETL logic and data pipelines.
Ensure the quality of every production release using a data-driven approach.
Develop and improve quality processes for delivering operational data.
Collaborate with Data Analysts, Product, and Engineering teams to deeply understand system behavior and business needs.
Translate technical specifications (calculations, custom groups, parameters, filters, aggregations) into test requirements.
Build automated and reusable tests for data stores to improve quality and development efficiency.
Diagnose issues, report defects, and propose regression tests to catch recurring bugs.
Mentor fellow Test Engineers to enhance automation capabilities and expand test coverage.
Basic Qualifications
3 - 5 years of experience in quality assurance for ETL pipelines and data warehouses.
Expertise in SQL and experience working with relational databases.
Strong background in data analytics, data engineering, data modeling, and big data platforms.
Proficiency in Scala/Java or scripting languages like Python.
Experience with testing frameworks such as JUnit, TestNG, BDD, or similar tools.
Hands-on experience with big data technologies like Airflow, Hive, Snowflake, Databricks, Spark.
Experience working with large datasets (terabytes or more).
Ability to work effectively in a team-oriented and collaborative environment.
Excellent communication skills with the ability to interact with both technical and non-technical stakeholders.
Preferred Qualifications
Preferred locations: West Coast, ideally Seattle/Santa Monica. However, for exceptional candidates, East Coast locations may also be considered.
In-office preference: If multiple candidates are equally qualified, preference may be given to those located closer to our offices.
Education
Bachelor s degree in Computer Science, Engineering, or a related field.
