Quality Engineer

Techblocks Inc.; New York, Northern (NY, KY); Hybrid; USD 110,000 - 170,000; Full time

Job summary

Techblocks Inc. is seeking an experienced Data Quality Engineer to ensure the reliability and accuracy of large-scale data platforms on Google Cloud. You will design testing strategies for pipelines, APIs, and databases, and automate validation with Python.

You will work across data ingestion, transformation, storage, and downstream consumption, performing API and UI testing with Playwright, and leading performance tests using k6 in a collaborative, product-focused team.

Qualifications

• Proven experience as a Data Quality Engineer or similar role on modern data platforms.
• Hands-on Python-based test automation and API testing expertise.
• Experience with Playwright for UI automation and with GCP data services.

Responsibilities

• Design and execute data quality and testing strategies for cloud platforms and pipelines.
• Validate end-to-end data pipelines from ingestion to downstream consumption.
• Perform data validation across streaming and batch pipelines for accuracy and consistency.
• Develop Python automation frameworks for API, backend, and data testing.
• Create UI automation tests with Playwright and perform manual validation when needed.
• Conduct REST API testing including functional, integration, and end-to-end validation.
• Plan and execute performance tests using k6 across pipelines and services.
• Validate data across PostgreSQL/AlloyDB, MongoDB, BigQuery, and other databases.
• Work within GCP (Pub/Sub, GCS, Dataflow, Dataproc, Cloud Composer).
• Troubleshoot data issues and collaborate with Data Eng, DevOps, and Product teams.
• Support CI/CD with automated data, API, and quality checks.

Skills

Data Quality Engineer

Python test automation

API testing

UI automation

GCP data tech

SQL validation

BigQuery

PostgreSQL/AlloyDB

MongoDB

Performance testing

Tools

k6

Playwright

Dataplex

ClickHouse

Job description

We are looking for an experienced Data Quality Engineer with strong expertise in cloud-based data platforms, data pipeline testing, API automation, performance testing, and database validation. The ideal candidate will be responsible for ensuring the quality, reliability, accuracy, and performance of large-scale data platforms and pipelines, with a strong focus on GCP and Python-based test automation.

Key Responsibilities

• Design and execute comprehensive data quality and testing strategies for cloud-based data platforms, pipelines, APIs, and applications.
• Validate end-to-end data pipelines, including data ingestion, transformation, processing, storage, and downstream consumption.
• Perform data validation across streaming and batch-processing pipelines, ensuring data accuracy, completeness, consistency, and integrity.
• Develop and maintain Python-based automation frameworks for backend, REST API, and data validation testing.
• Develop UI automation tests using Playwright and perform manual validation where required.
• Perform RESTful API testing, including functional, integration, negative, regression, and end-to-end validation.
• Design and execute performance, load, stress, latency, and throughput testing using tools such as k6.
• Validate data across relational, document, analytical, and columnar databases, including PostgreSQL/AlloyDB, MongoDB, BigQuery, and optionally ClickHouse.
• Work extensively within the Google Cloud Platform (GCP) ecosystem, including Pub/Sub, GCS, Dataflow, Dataproc, and Cloud Composer.
• Troubleshoot data discrepancies, pipeline failures, API issues, and performance bottlenecks, collaborating closely with Data Engineering, Development, DevOps, and Product teams.
• Build automated reconciliation and data-validation checks to identify missing, duplicate, inconsistent, incorrect, or delayed data.
• Contribute to CI/CD processes by integrating automated data, API, and application quality checks into deployment pipelines.
• Support data profiling, governance, cataloging, lineage, and automated data-quality controls, preferably using Dataplex.

Required Skills

• Strong experience as a Data Quality Engineer, SDET, Data Test Engineer, or QA Automation Engineer working with modern data platforms.
• Strong hands-on experience with Python-based test automation.
• Strong experience testing RESTful APIs and backend services.
• Experience with Playwright or similar UI automation frameworks.
• Hands-on experience with GCP data technologies, particularly Pub/Sub, GCS, Dataflow, Dataproc, Cloud Composer, and BigQuery.
• Strong SQL and data-validation skills with experience working across large and complex datasets.
• Experience with PostgreSQL/AlloyDB, MongoDB, and BigQuery.
• Hands-on performance testing experience using k6 or comparable modern load-testing tools.
• Strong understanding of ETL/ELT, batch and streaming pipelines, data reconciliation, schema validation, and data-quality principles.
• Strong analytical, debugging, problem-solving, and cross-functional communication skills.

Nice to Have

• Experience with ClickHouse or other high-performance columnar databases.
• Experience with Dataplex for data profiling, cataloging, governance, and automated data-quality controls.
• Experience integrating automated tests into CI/CD pipelines.
• Knowledge of data observability, data lineage, metadata management, and cloud-native monitoring