Data Platform Engineer: Build Scalable Cloud Pipelines

Sigma Computing; New York (NY); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Equity

Flexible time off

Paid bonding time for new parents

Traditional and Roth 401k

Commuter and FSA benefits

Lunch Program

Dog friendly office

Job summary

Sigma Computing is building out its Data Platform team to develop data models that fuel trusted insights across the company. As a Data Platform Engineer, you’ll own the underlying data architecture across Snowflake and Databricks and build ETL pipelines for internal and demo use cases.

You’ll report to the Head of Data and work with Product, Engineering, and GTM teams to enable scalable data governance, reliability, and fast iteration on greenfield projects.

Qualifications

• 3+ years of relevant experience working in a data engineering role.
• Experience with APIs and building data pipelines into Cloud Data Platforms.
• Strong communication and collaboration with Analytics and Infra teams.
• Experience deploying data governance frameworks.
• Ability to thrive in ambiguous environments and move fast.
• Startup experience.

Responsibilities

• Architect and manage production data pipelines in Snowflake and Databricks.
• Build scalable demo asset data pipelines across cloud data warehouses.
• Partner with infrastructure engineering to ensure high availability of key data assets.
• Implement and scale data governance policies.
• Collaborate across Product, Engineering, and GTM teams.

Skills

APIs

Data pipelines

Collaboration

Data governance

Ambiguity tolerance

Startup experience

Tools

Snowflake

Databricks

Fivetran

dbt

Hightouch

Metaplane

Job description

Sigma Computing is building out its Data Platform team to develop data models that fuel trusted insights across the company. As a Data Platform Engineer, you’ll own the underlying data architecture across Snowflake and Databricks and build ETL pipelines for internal and demo use cases.

You’ll report to the Head of Data and work with Product, Engineering, and GTM teams to enable scalable data governance, reliability, and fast iteration on greenfield projects.