Company Description
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.
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Job Description
We are looking for an experiencedSenior Data Engineer with a strong foundation inPython, SQL, and Snowflake , and hands-on expertise inBigQuery, Databricks .
In this role, you will build and maintain scalable data pipelines and architecture to support analytics, data science, and business intelligence initiatives.
You’ll work closely with cross-functional teams to drive data reliability, quality, and performance.
Responsibilities:
- Contribute to the design and architecture of a lakehouse solution, potentially leveraging technologies such asIceberg ,Snowflake , andBigQuery .
- Build and maintain robustETL/ELT workflows usingPython andSQL to handle structured and semi-structured data.
- Partner with data scientists and analysts to provide high-quality, accessible, and well-structured data.
- Ensure data quality, governance, security, and compliance across pipelines and data stores.
- Monitor, troubleshoot, and improve the performance of data systems and pipelines.
- Participate in code reviews and help establish engineering best practices.
- Mentor junior data engineers and support their technical development.
Qualifications
- Studies in computer science, Engineering, or a related field.
- 5+ years of hands-on experience indata engineering , with at least 2 years working withBigquery or Snowflake .
- Strong programming skills inPython for data processing and automation.
- Advanced proficiency inSQL for querying and transforming large datasets.
- Solid understanding of data modelling, warehousing, and performance optimization techniques.
- Proven experience in data cataloging and inventorying large-scale datasets.
- Hands-on experience implementing and working with Medallion architecture in data lakehouse environments
- Iceberg, Data Mesh experience, dbt (Those are a Plus)
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