Blend
Website:
blend360.com
Job details:
Job Description
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.
What is this position about?
- 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 optimization, 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.
Qualifications
- 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.
Additional Information
- 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.
Click on Apply to know more.