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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
Job DescriptionYou will be a part of our Data Engineering team and will be focused on delivering exceptional results for our clients. A large portion of your time will be in the weeds working alongside your team architecture, designing, implementing, and optimizing data solutions. You’ll work with the team to deliver, migrate and/or scale cloud data solutions; build pipelines and scalable analytic tools using leading technologies including AWS, Azure, GCP, Spark, Hadoop, etc.
What you’ll be doing?
- Develop data pipelines to move and transform data from various sources to data warehouses
- Ensure the quality, reliability, and scalability of the organization's data infrastructure
- Optimize data processing and storage for performance and cost-effectiveness
- Collaborate with data scientists, analysts, and other stakeholders to understand their requirements and develop solutions to meet their needs
- Continuously monitor and troubleshoot data pipelines to ensure their reliability and availability
- Stay up to date with the latest trends and technologies in data engineering and apply them to improve our data capabilities
- Bachelor’s degree in computer science, Software Engineering, or a related field
- 6+ years of experience in data engineering or a related field
- Strong programming skills in Python or Scala or Java
- Expert SQL skills and a good understanding of existing SQL warehouses
- Familiarity with big data technologies like Hadoop, Spark, or Hive
- Experience with cloud-based data storage and processing platforms like AWS, Azure, or GCP
- Strong problem-solving and communication skills
