Data Engineer (AI)

Location: New York, United States

Salary: $196K–$257.2K annually

Company

Snowflake provides the AI Data Cloud and develops data engineering, analytics, and AI capabilities for enterprise customers.

What you will do

• Advise customers on Snowflake data engineering best practices and architect Snowflake-centric solutions for modernization and migration initiatives.
• Design, build, deploy, monitor, and optimize production data pipelines across ingestion, transformation, orchestration, governance, data modeling, and data quality.
• Develop proof-of-concepts and reference implementations using SQL, Python, Snowpark, dbt, and agentic development tools.
• Apply AI coding agents and Snowflake AI capabilities to accelerate pipeline development, code conversion, testing, documentation, migrations, and operations.
• Create repeatable agent-driven delivery patterns and accelerators, transfer knowledge to customers, and support Services Delivery team members.
• Collaborate with customers, Systems Integrators, Product Management, Engineering, and Marketing while providing feedback on product and agentic feature roadmaps.

Requirements

• At least 5 years of experience working with customers in a pre-sales or post-sales technical role.
• Outstanding presentation skills for technical and executive audiences, including whiteboarding, presentations, and demos.
• Thorough knowledge of the complete data engineering lifecycle, including ingestion, transformation, orchestration, data modeling, and data quality.
• Thorough knowledge of modern data architecture patterns, including batch and streaming pipelines, ELT, lakehouse and open table formats such as Apache Iceberg, and data warehouse migration and modernization.
• Strong understanding of DataOps, CI/CD, observability, performance tuning, cost optimization, testing, monitoring, and governance for data pipelines.
• Hands-on experience applying AI coding agents and agentic workflows to data engineering work.
• Experience with at least one public cloud platform: AWS, Azure, or GCP.
• Experience with at least one data platform or integration technology, such as Databricks, AWS Glue/EMR, Azure Data Factory/Synapse, GCP BigQuery/Dataflow, Informatica, or Fivetran.
• Hands-on SQL scripting and experience with at least one of Python, Java, or Scala; experience with tools such as dbt, Apache Spark/PySpark, Apache Airflow, Kafka, or Pandas.
• University degree in computer science, engineering, data science, mathematics, or a related field, or equivalent experience.

Nice to have

• Experience migrating Databricks, Apache Spark, or legacy ETL workloads such as Informatica, SSIS, or DataStage to Snowflake.
• Experience building agentic workflows, custom agent skills, or MCP-based tooling for data engineering automation.
• Experience with AI/ML workloads, including feature engineering data preparation, RAG, agent use cases, and ML/DL fundamentals.
• Snowflake certifications such as SnowPro Advanced: Data Engineer or Architect.
• Proven success in enterprise software and vertical expertise in FSI, Retail, Manufacturing, or a similar core vertical.

Culture & Benefits

• AI-native, experimental approach to solving problems and accelerating delivery.
• Low-ego, fast-moving environment focused on challenging ordinary thinking and innovation.
• Confidentiality and security standards are essential parts of the role, including protecting customer information.
• Opportunities to influence Snowflake products, marketing, and the roadmap for data engineering and agentic features.