IT Trailblazers, LLC.

Compensation

Full Description

Role Overview The API & Data Pipeline Quality Engineer is responsible for ensuring the reliability, scalability, and data integrity of enterprise APIs and cloud-based data platforms. This role drives end-to-end quality engineering practices across API services, data pipelines, and analytical environments, with a strong focus on automation, observability, and modern cloud architectures using AWS. Key Responsibilities API Quality Engineering Design and execute automated testing strategies for RESTful and event-driven APIs. Validate functional, integration, and contract testing across distributed services. Develop automation frameworks using modern tools (e.g., Python, Playwright, Postman, REST Assured, or similar). Perform performance, resilience, and security validation for APIs. Collaborate with developers to embed quality early in CI/CD pipelines. Data Pipelines & Data Quality Validate ETL/ELT pipelines and transformations within cloud data platforms (e.g., Snowflake, Redshift, AWS Aurora Postgres, SQL). Design automated data validation checks for completeness, accuracy, lineage, and reconciliation. Develop SQL and Python-based validation frameworks to verify large-scale datasets. Ensure governance standards such as RBAC, data privacy, and auditability are maintained. Support testing for reporting and analytics layers (BI dashboards, semantic models, datasets) Automation & DevOps Integration Integrate testing into CI/CD pipelines using GitHub Actions, Jenkins, or similar tools. Implement data quality automation and monitoring using modern frameworks built using Python. Drive shift-left testing practices across engineering squads. Contribute to infrastructure testing in cloud environments (AWS). Collaboration & Program Alignment Partner with API developers, data engineers, and product teams to define acceptance criteria and test strategies. Participate in architecture reviews and provide quality risk assessments. Provide test metrics aligned with engineering KPIs (e.g., DORA metrics, automation coverage, defect leakage). Required Qualifications Bachelor s degree in Computer Science, Engineering, or related field. Experience in API testing and automation frameworks. Strong SQL skills with hands-on experience validating data pipelines or data warehouse models. Knowledge of cloud data platforms such as Snowflake, AWS Postgres, Glue, Redshift, or equivalent. Experience working within Agile/Scrum delivery models. Preferred Qualification Experience with data quality tools (e.g., iCEDQ, Great Expectations, custom frameworks). Exposure to event-driven architectures or streaming platforms. Understanding of observability and monitoring tools. Familiarity with infrastructure-as-code or cloud networking concepts. Experience validating large-scale datasets and enterprise reporting solutions. Core Competencies Strong analytical and problem-solving skills. Ability to work across API, data, and platform engineering teams. Automation-first mindset with a focus on scalable solutions. Executive-level communication and stakeholder collaboration.