Data Quality Engineer

🕒 May 1

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Blend360

WebsiteLinkedInAll Job Openings

501 - 1000 employees

🤖 Artificial Intelligence

🏢 Enterprise

💰 $100M Private Equity Round on 2022-08

Artificial Intelligence • Enterprise • Consulting

Blend360 is a professional services company specializing in AI, data analytics, and data-driven solutions. They work with Fortune 1000 and large enterprise brands to tackle significant challenges by integrating people and artificial intelligence. Blend360 focuses on several domains including business intelligence, data engineering, data science, MLOps, and data governance. Their industries of expertise encompass financial services, energy, healthcare and life sciences, retail, technology, media & telecom, and travel & hospitality. Blend360 is recognized for their AI and data solutions, having earned accolades such as "AI-Enabling Solution of the Year" and being listed among the "Top Generative AI Service Providers 2024.

📋 Description

• Ensure data quality, reliability, and consistency across modern data platforms. • Validate data pipelines and implement automated quality checks. • Collaborate closely with Data Engineering and business teams. • Design and implement a data quality framework. • Build and maintain automated data quality checks within Databricks pipelines. • Own reconciliation between source systems and Databricks layers. • Validate identity resolution outputs in the Silver layer. • Perform end-to-end pipeline testing. • Partner with Data Engineers to define acceptance criteria. • Support UAT with client business stakeholders. • Document QA processes, test results, and findings. • Monitor pipeline health post-deployment and resolve incidents.

🎯 Requirements

• Experience working with Azure-based data platforms, including Databricks. • Strong understanding of data quality frameworks and testing methodologies for data pipelines. • Experience validating ETL/ELT processes and working with layered architectures (Bronze, Silver, Gold). • Strong SQL skills and experience analyzing large datasets. • Experience implementing automated data validation and reconciliation processes. • Familiarity with data pipeline monitoring, alerting, and troubleshooting. • Ability to collaborate with Data Engineers and business stakeholders. • Strong analytical thinking and attention to detail. • Experience documenting QA processes and results in a structured manner. • English: Advanced (required for effective communication with global teams).

🏖️ Benefits

• 📚Learning Opportunities: Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. • Access to AI learning paths to stay up to date with the latest technologies. • Study plans, courses, and additional certifications tailored to your role. • Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. • English lessons to support your professional communication. • 👨🏽‍💻Travel opportunities to attend industry conferences and meet clients. • 👩‍🏫 Mentoring and Development: Career development plans and mentorship programs to help shape your path. • 🎁 Celebrations & Support: Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. • Company-provided equipment. • ⚖️ Flexible working options to help you strike the right balance.