Remote Data Engineer - Databricks & ML Pipelines

Openkrill; United States; Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Remote-first culture – work from anyw🚀

AWS, DBT, Google Cloud, Azure & Databr

In-Company English Lessons.

Birthday off + an extra vacation week

Referral bonuses – help us grow the 팀

Job summary

Muttdata, a remote-first startup, builds Data Products and ML solutions for diverse clients, including a major multinational beverage company based in Mexico City. We seek a Data Engineer to join high-impact projects and advance our data platform for enterprise-scale use cases.

You will co-develop batch and streaming pipelines on Databricks using Python and Spark, define data contracts and data quality rules, and mentor domain engineers on data product ownership and best practices.

Qualifications

• Experience building and optimizing data pipelines.
• Proficient with Databricks, Python and Spark for batch/streaming.
• Familiarity with BI tools Looker or Tableau.

Responsibilities

• Co-develops batch and streaming pipelines on Databricks (Python/Spark).
• Defines and maintains data contracts, quality rules, and data SLOs for each data product.
• Guides domain teams on data modeling and data product boundaries (what belongs to which product/domain).
• Trains, mentors and pairs with domain engineers/analysts on data product ownership and good engineering practices.
• Captures feedback and best practices from domains and feeds improvements back into platform templates, tooling, and patterns.

Skills

Data pipelines

Python

Spark

Databricks

Looker

Tableau

Tools

Databricks

Looker

Tableau

Job description

Muttdata, a remote-first startup, builds Data Products and ML solutions for diverse clients, including a major multinational beverage company based in Mexico City. We seek a Data Engineer to join high-impact projects and advance our data platform for enterprise-scale use cases.

You will co-develop batch and streaming pipelines on Databricks using Python and Spark, define data contracts and data quality rules, and mentor domain engineers on data product ownership and best practices.