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Data Engineer ( Data Bricks)

Della Infotech Inc
Beaverton, OR, United States
9 days ago
Apply on www.dice.com
Prepare application

Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Job source
www.dice.com

Tech stack

Airflow Amazon Web Services Microsoft Azure Computer Programming Continuous Integration Information Engineering Extract Transform Load (ETL) Data Warehousing DevOps Apache Hive Python (Programming Language) Performance Tuning
+10 more
SQL Databases Data Streaming Workflow Management Systems Google Cloud Git Data Lakes Pyspark Information Technology Data Pipelines Databricks

Requirements

  • 14+ years of IT experience with 10+ years in Data Engineering.
  • Mandatory hands-on experience in Databricks (PySpark, Spark SQL, Delta Lake).
  • Customer Management including Escalation, Issue resolution (Mandatory)
  • Strong programming skills in Python and SQL.
  • Experience building scalable ETL/ELT pipelines and data engineering solutions.
  • Hands-on experience with Azure/AWS/Google Cloud Platform, preferably Azure, and orchestration tools (ADF/Airflow).
  • Strong understanding of data modeling, data warehousing, and performance optimization.
  • Experience with Git, CI/CD, and DevOps best practices.
  • Knowledge of Delta Live Tables, Unity Catalog, and Structured Streaming is preferred.
  • Ability to collaborate with business and cross-functional teams to deliver enterprise data solutions.
  • Excellent analytical, problem-solving, and communication skills

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.dice.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

Explore playlists

2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon · World Congress 2026 Europe

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · World Congress 2026 Europe

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

3:05 min

Audience questions on AI agents and pipeline vectorization

Joy Joy · World Congress 2024

3:18 min

Scaling global network engineering through DevOps culture

Stuart Clark · LIVE

Videos

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From Messy Queries to Scalable Systems - How Data Engineering actually works thumbnail
31:15
World Congress 2026 Europe • about 2 months ago

From Messy Queries to Scalable Systems - How Data Engineering actually works

Sandhya Menon

From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform thumbnail
22:57
World Congress 2026 Europe • about 2 months ago

From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform

Dominik Krichbaum

How a Small Team Shrank a Microsoft Monorepo by 94% thumbnail
33:23
Coffee With Developers • almost 2 years ago

How a Small Team Shrank a Microsoft Monorepo by 94%

Jonathan Creamer

Enjoying SQL data pipelines with dbt thumbnail
26:53
World Congress 2023 • almost 3 years ago

Enjoying SQL data pipelines with dbt

Matthias Niehoff

AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment thumbnail
25:41
World Congress 2024 • about 2 years ago

AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment

Joy

DevOps Maturity Check – a way to balance autonomy and alignment thumbnail
42:52
LIVE • almost 6 years ago

DevOps Maturity Check – a way to balance autonomy and alignment

Martin Thalmann

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