Senior Data Engineer — Databricks & Cloud Pipelines

Talenzaa; Glendale (CA); In loco; USD 102.000 - 170.000; Tempo pieno

Descrizione del lavoro

Talenzaa seeks a Senior Data Engineer to join its Data Platform team in Glendale, CA. You will design scalable cloud-based data platforms and modern data pipelines, collaborating with data engineers, architects, PMs, and data scientists to support BI, analytics, and ML initiatives.

The role requires hands-on work with Databricks, Spark, Airflow MWAA, and AWS, along with governance and containerization. Onsite in Glendale with competitive benefits.

Competenze

• 5+ years of data engineering experience building and operating large-scale data pipelines.
• Hands-on experience with Databricks and Apache Spark (batch and streaming).
• Strong SQL skills with performance tuning and optimization.

Mansioni

• Design, write, test, and deploy data pipelines using PySpark, Scala, SQL, Python.
• Collaborate with stakeholders to translate requirements into scalable data platform solutions.
• Explain Spark architecture and pipeline behavior to diagnose issues and propose solutions.
• Provide solution architecture across AWS, Databricks, Kubernetes, and Airflow (MWAA).
• Manage Databricks governance (Unity Catalog, ACLs, lineage) and data privacy tooling.
• Build and maintain Kubernetes containers supporting data platform services.
• Monitor platform health, cost, and access, and document changes for governance.

Conoscenze

Databricks experience

Advanced SQL

PySpark/Scala

Python

Airflow (MWAA)

AWS

Docker and Kubernetes

Formazione

Bachelor's Degree in Computer Science / Information Systems or related field

Strumenti

Databricks tooling (API/SDK/CLI)

Airflow MWAA

Docker

Kubernetes

Snowflake

Descrizione del lavoro

Talenzaa seeks a Senior Data Engineer to join its Data Platform team in Glendale, CA. You will design scalable cloud-based data platforms and modern data pipelines, collaborating with data engineers, architects, PMs, and data scientists to support BI, analytics, and ML initiatives.

The role requires hands-on work with Databricks, Spark, Airflow MWAA, and AWS, along with governance and containerization. Onsite in Glendale with competitive benefits.