Lead Data Engineer - Azure & Databricks

8451; Cincinnati (OH); On-site; USD 125,000 - 207,000; Full time

Benefits offered by this job

Health insurance

401(k) with Roth option

Paid time off

Job summary

84.51° is seeking a Lead Data Engineer to design and implement big data ingestion, storage, and distribution on Azure Cloud. You will use Databricks, PySpark, Python, JSON and SQL to build customer personalization tools, collaborating with Product and Data Science to deliver scalable enterprise applications.

You will mentor engineers, define technical strategy, and drive REST API development in Kubernetes, while aligning with cross-functional teams and Agile planning.

Qualifications

• Bachelor’s degree in Computer Science, MIS, Mathematics, Business Analytics or a similarly strong program.
• 5+ years of professional data development experience.
• Solid understanding of Agile principles (Scrum).
• 5+ years developing with Spark (Databricks, PySpark).
• Proficient in Python and REST APIs; Kubernetes experience preferred.

Responsibilities

• Take ownership of features and drive them to completion through all phases of the SDLC.
• Develop business domain understanding and bridge to technical stakeholders.
• Set technical strategy in partnership with Data Science, Product, Architecture, and Kroger partners.
• Oversee teams of engineers, including offshore/onshore resources.
• Provide mentoring to junior developers.
• Lead design and development of Databricks-based solutions.
• Develop REST APIs hosted in Kubernetes.
• Execute unit and integration testing.
• Maintain consistent development practices with senior staff.
• Bring new perspectives and continuously improve processes.

Skills

Spark / PySpark

REST APIs

Kubernetes

Python

Agile (Scrum)

Databricks

Education

Bachelor’s degree in Computer Science, MIS, Mathematics, or Business Analytics

Tools

Databricks

Job description

84.51° is seeking a Lead Data Engineer to design and implement big data ingestion, storage, and distribution on Azure Cloud. You will use Databricks, PySpark, Python, JSON and SQL to build customer personalization tools, collaborating with Product and Data Science to deliver scalable enterprise applications.

You will mentor engineers, define technical strategy, and drive REST API development in Kubernetes, while aligning with cross-functional teams and Agile planning.