Cloud Data Engineer - Lakehouse & Real-Time Pipelines

Oscar; Grand Prairie (TX); On-site; USD 110,000 - 150,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

15 days of PTO

401(k) enrollment

Relocation assistance

Job summary

Oscar is seeking an experienced Data Engineer to design and maintain scalable cloud data pipelines supporting high-volume manufacturing and IoT data. The ideal candidate has 5+ years of Data Engineering experience, strong SQL and Python skills, and hands-on experience with scalable data pipelines.

This role involves building batch and real-time processing solutions using Spark/PySpark and working with cloud platforms like Databricks and Snowflake.

Qualifications

• 5+ years of professional Data Engineering experience; additional experience is welcome for the right candidate.
• Strong proficiency in SQL and Python.
• Hands-on experience building scalable data pipelines.
• Experience with Lakehouse and/or Medallion architectures.
• Strong understanding of ETL/ELT, data integration, and data transformation.

Responsibilities

• Design, develop, and maintain scalable cloud data pipelines for high-volume data.
• Build batch and real-time data processing solutions using Spark/PySpark, Kafka, and Airflow.
• Develop data ingestion, transformation, and integration workflows using SQL and Python.
• Process and integrate large volumes of manufacturing, operational, and IoT data.
• Troubleshoot data pipeline issues and improve data quality and performance.

Skills

SQL

Python

Data Engineering

Apache Spark

Apache Kafka

Airflow

Lakehouse architecture

Medallion architecture

ETL/ELT

Data integration

Tools

Databricks

Snowflake

AWS

Azure

Delta Lake

Job description

Oscar is seeking an experienced Data Engineer to design and maintain scalable cloud data pipelines supporting high-volume manufacturing and IoT data. The ideal candidate has 5+ years of Data Engineering experience, strong SQL and Python skills, and hands-on experience with scalable data pipelines.

This role involves building batch and real-time processing solutions using Spark/PySpark and working with cloud platforms like Databricks and Snowflake.