🕒 yesterday
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines, collaborating closely with Data Scientists and ML Engineers to enhance production workflows.
Senior Databricks Data Engineer
📅 Jul 29
DatabricksAzure DatabricksLakehouse ArchitectureETL
📜 Description
- Design and implement ETL/ELT pipelines using Azure Databricks.
- Utilize Lakehouse architecture for data management.
- Work with Delta Live Tables (DLT) for data processing.
- Leverage PySpark for data engineering tasks.
- Collaborate with local Austin team members for in-person meetings.
🛠️ Requirements
- ✔️ Databricks Certified Data Engineer (Associate or Professional)
- ✔️ Azure Databricks
- ✔️ Lakehouse Architecture
- ✔️ ETL / ELT Pipelines
- ✔️ Delta Live Tables (DLT)
- ✔️ Data Engineering
- ✔️ Local Austin candidates who can attend an in-person interview
Full job description
Senior Databricks Data Engineer (Azure Databricks | Lakehouse | ETL/ELT)
📍 Austin, Texas (Hybrid – 3 Days Remote | Onsite Every Monday & Thursday)
Experience: Minimum 12+ Years
Mandatory Requirements
✔️ Databricks Certified Data Engineer (Associate or Professional)
✔️ Azure Databricks
✔️ Lakehouse Architecture
✔️ ETL / ELT Pipelines
✔️ Delta Live Tables (DLT)
✔️ PySpark
✔️ Data Engineering
✔️ Local Austin candidates who can attend an in-person interview
Similar jobs
Search more Data Engineer jobs🕒 yesterday
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines, focusing on Python, AWS, and ETL processes to enhance data-driven solutions.
🕒 yesterday
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines, focusing on Python, AWS, and ETL processes to enhance data-driven decision-making.
🕒 yesterday
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines, collaborating with Data Scientists and ML Engineers to enhance production workflows.
🕒 yesterday
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines, collaborating with Data Scientists and ML Engineers to enhance production workflows.