Data Engineer

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com

We are looking for a forward-thinking Data & AI Engineer with 1–3 years of experience in data engineering and a passion for using modern AI tools to accelerate development workflows. The ideal candidate is proficient in Python, SQL, PySpark, and has experience working in on-premise big data environments (e.g., Spark, Hadoop, Hive, HDFS). This role is ideal for someone eager to blend traditional data engineering practices with AI-augmented software development, helping us build high-performance pipelines and deliver faster, smarter solutions. 

What you’ll be doing 

• Develop and maintain robust ETL/ELT pipelines using Python, SQL, and PySpark. 

• Work with on-premise big data platforms such as Spark, Hadoop, Hive, and HDFS. 

• Optimize and troubleshoot workflows to ensure performance, reliability, and quality. 

• Use AI tools to assist with code generation, testing, debugging, and documentation. 

• Collaborate with data scientists, analysts, and engineers to support data-driven use cases. 

• Maintain up-to-date documentation using AI summarization tools. 

• Apply AI-augmented software engineering practices, including automated testing, code reviews, and CI/CD. 

• Identify opportunities for automation and process improvement across the data lifecycle. 

• 1–3 years of hands-on experience as a Data Engineer or in a similar data-focused engineering role. 

• Proficiency in Python for data manipulation, automation, and scripting. 

• Solid understanding of SQL and relational database design. 

• Experience building distributed data processing solutions with PySpark. 

• Familiarity with on-premise big data ecosystems, including Hadoop, Hive, HDFS. 

• Active use of AI development tools, such as: 

• GitHub Copilot, Windsurf, Cursor – for intelligent code assistance 

• ChatGPT or similar – for testing support, refactoring, and documentation 

• AI-based testing frameworks or custom scripts 

• Familiar with Git and CI/CD pipelines. 

• Strong analytical skills and a mindset for automation and innovation.