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 an experienced Snowflake Manager to lead a high-performing team of data engineers, own client relationships, and drive end-to-end cloud data platform strategy. The ideal candidate brings deep expertise in Snowflake, AWS, and Python, with hands-on experience across data lake and clean room architecture, identity resolution, ETL/ELT pipelines, and MLOps. This role requires someone equally strong in technical leadership and people management — setting direction, delivering through teams, and ensuring referenceable outcomes for stakeholders.

Key Responsibilities

• Directly manage a team of data engineers — overseeing performance, career development, and team dynamics; leading multiple concurrent projects to scope, timeline, and quality; and delivering constructive feedback with support from senior leadership.
• Own client and stakeholder relationships within assigned accounts, ensuring referenceable outcomes and managing nonstandard situations with senior support where needed.
• Design and implement Snowflake data warehouse architecture, data lake, and clean room frameworks, including identity resolution strategies, ID join logic, and master lookup tables across heterogeneous data sources.
• Build and maintain core data tables and ETL/ELT pipelines from multiple source types (network, device, media/video), covering ingestion, transformation, and data quality validation.
• Architect AWS cloud data solutions (S3, Glue, Kinesis, Lambda, Step Functions), including dev/prod environment setup, CI/CD pipelines, and workflow orchestration via Airflow or AWS-native services.
• Drive MLOps, pipeline automation, and platform reliability — including Snowflake performance tuning, storage optimisation, capacity planning, and onboarding of new data sources.
• Enforce data governance, security, and privacy standards across all pipelines, including AWS IAM policies, encryption, and data quality controls.
• Collaborate with analysts, product, and business stakeholders to translate requirements into efficient data models and solutions.

• 7+ years of experience in Data Engineering or Data Platform roles, with a track record of managing engineers and delivering at scale.
• Deep hands-on expertise in Snowflake — architecture, performance tuning, data modeling, warehouse setup, and data lake / clean room design.
• Strong command of the AWS ecosystem (S3, Glue, Lambda, Kinesis, Step Functions, IAM, CloudWatch) and proficiency in Python (Pandas, PySpark) and SQL.
• Experience with ETL/ELT frameworks, workflow orchestration (e.g. Airflow), CI/CD pipelines, and entity identity resolution across disparate data sources.
• Familiarity with MLOps frameworks and pipeline automation for integrating machine learning workflows into data engineering pipelines.
• Excellent problem-solving, communication, and stakeholder management skills.

• Background in network, device, or media/video data within a telecommunications, ISP, or media analytics environment.
• Experience with streaming technologies (Kafka / Kinesis).
• Exposure to the Snowflake AI and developer stack — Snowpark, Snowflake Cortex, Snowflake Intelligence, or other native ML/AI capabilities.
• AWS or Snowflake certifications.