Blend360
AI services
DataEngineeringLead
Neural analysis suggests this role is
optimal for mid candidates.
“Data Engineering Lead at Blend360. Skills: Snowflake-based data platforms, Modern data architectures, AWS, Data ingestion architectures, ELT pipelines, Data quality frameworks, Medallion Architecture. Lead the design and implementation of data ingestion architectures in Snowflake, ensuring scalability and reliability.. Own the development of end-to-end ELT pipelines integrating multiple data sources.”
What You'll Achieve.
Ensuring high-quality, governed, and reliable data pipelines that power critical business and analytics workflows.
Industry & Context.
Analytical thinking & problem-solving; Proactiveness – ability to anticipate issues and act before they become blockers.
Travel opportunities to attend industry conferences and meet clients.
What They're Looking For.
Must Have
4+ years of experience in Data Engineering, hands-on experience with Snowflake, experience building ELT pipelines and data ingestion solutions, Solid experience with SQL and large-scale data processing, understanding and hands-on experience with Medallion Architecture
Nice to Have
Experience building and maintaining data pipelines in AWS, Familiarity with Snowflake Cortex, Experience with CI/CD pipelines for data workflows, Experience with Iceberg tables and Snowflake data sharing, Experience with tools such as dbt, Glue, Athena, EMR, Lambda, Terraform, or CloudFormation
What You'll Do.
Lead the design and implementation of data ingestion architectures in Snowflake
ensuring scalability and reliability.
Own the development of end-to-end ELT pipelines integrating multiple data sources.
Design and enforce data quality frameworks
including validation rules
Apply and drive Medallion Architecture (Bronze
Gold) best practices across data pipelines.
Build and optimize data pipelines and architectures on AWS (S3
Develop and enhance data validation and ingestion frameworks
including UI components (Streamlit-based) when needed.
Act as a technical leader
guiding best practices in data engineering
and pipeline reliability.
Proactively identify risks
and data quality issues
and implement mitigation strategies before they impact delivery.
Contribute to data governance initiatives
including data definitions
and stewardship practices.
Drive documentation and continuous improvement of data platform processes.
How You'll Work.
Team & Collaboration
Ability to work directly with clients and cross-functional teams.
Communication Scope
Ability to work directly with clients and cross-functional teams; Client-facing mindset – comfortable engaging with stakeholders and driving discussions
Full Job 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. For more information, visit [www.blend360.com](http://www.blend360.com/) We’re looking for a Lead Data Engineer with strong expertise in Snowflake-based data platforms , modern data architectures, and AWS, to lead the design and implementation of scalable ingestion and validation solutions for a leading enterprise client. This is a client-facing leadership role , ideal for engineers who combine deep technical expertise with strong communication skills and a proactive mindset. You will play a key role in ensuring high-quality, governed, and reliable data pipelines that power critical business and analytics workflows. What will you be doing? * Lead the design and implementation of data ingestion architectures in Snowflake , ensuring scalability and reliability. * Own the development of end-to-end ELT pipelines integrating multiple data sources. * Design and enforce data quality frameworks , including validation rules, testing strategies, and monitoring. * Apply and drive Medallion Architecture (Bronze, Silver, Gold) best practices across data pipelines. * Build and optimize data pipelines and architectures on AWS (S3, Glue, Lambda, EMR, etc.). * Develop and enhance data validation and ingestion frameworks , including UI components (Streamlit-based) when needed. * Act as a technical leader , guiding best practices in data engineering, governance, and pipeline reliability.
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