Data Engineer Senior

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 Description

We’re looking for a Lead Data Engineer to support the design, development, and optimization of data solutions for a high-impact enterprise initiative. This role will focus on preparing and enabling the Snowflake data required for a Dataiku PO agent Proof of Concept (POC).

The ideal candidate has strong hands-on experience with Snowflake, SQL, data modeling, and data quality validation. You will be responsible for ensuring that data is properly ingested, transformed, standardized, and structured to support the POC and its downstream analytical workflows.

You will work closely with technical and business stakeholders to deliver reliable, high-quality datasets and scalable data pipelines that meet the initiative’s requirements.

Responsibilities

Prepare, structure, and enable the Snowflake data required to support the Dataiku PO agent POC.; Design, develop, and maintain data pipelines to ingest, transform, normalize, and prepare data from multiple sources.; Design and implement data ingestion workflows in Snowflake, ensuring scalability, reliability, and maintainability.; Develop and maintain data models that support analytical use cases and the requirements of the POC.; Implement data quality checks and validation rules to ensure data accuracy, consistency, completeness, and reliability.; Use SQL and Python to process, transform, and validate large datasets efficiently.; Identify and resolve data inconsistencies, anomalies, and structural issues that could affect downstream consumption.; Support ETL processes and file-handling workflows for structured and semi-structured data.; Collaborate with business and technical stakeholders to understand data requirements and translate them into reliable data solutions.; Contribute to technical documentation and continuously improve data processes, standards, and validation practices.

Requirements

5+ years of experience in Data Engineering or Data Analytics roles with a strong engineering focus.; Strong hands-on experience with Snowflake (must-have) .; Strong SQL skills, including data transformation, querying, and validation.; Experience with data modeling and preparing datasets for analytical and downstream applications.; Proven experience in data quality validation , including implementing checks to ensure accuracy, consistency, and completeness.; Experience building and maintaining ETL pipelines and data ingestion workflows.; Hands-on experience with Python for data processing and transformation.; Strong attention to detail and a focus on data reliability and quality.; Ability to collaborate effectively with technical and business stakeholders.

Nice to have

Experience integrating or connecting Snowflake with Dataiku .; Familiarity with AI-driven or agent-based proof-of-concept initiatives.

Benefits

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.; Career development plans and mentorship programs to help shape your path.; Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.; Company-provided equipment.