Data Engineer

DPP Tech, Inc.
San Francisco, CA, United States
14 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Adaptable Database Systems Airflow Data Analysis BigQuery Cloud Storage Information Engineering Extract Transform Load (ETL) Data Transformation Data Systems Data Warehousing Database Queries Software Debugging
+14 more
Dimensional Modeling Data Flow Control Operational Databases Performance Tuning Scrum Methodology Cloud Services SQL Databases Data Processing Google Cloud Sql Optimization Data Build Tool (dbt) Git Data Management Data Pipelines

Job description

We are seeking experienced Data Engineers with strong expertise in Google Cloud Platform (Google Cloud Platform) to design, develop, and maintain scalable data pipelines and modern cloud-based data platforms. The ideal candidate should have hands-on experience with BigQuery, Apache Airflow, SQL, DBT (Data Build Tool), and Google Cloud Platform services., * Design, develop, and optimize cloud-native data pipelines on Google Cloud Platform.

  • Build and maintain ELT workflows using DBT and Airflow.
  • Develop scalable data models in BigQuery.
  • Optimize SQL queries and improve data processing performance.
  • Collaborate with analytics, BI, and application teams to deliver high-quality data solutions.
  • Monitor, troubleshoot, and enhance production data pipelines.
  • Mentor junior engineers (Lead role).

Requirements

  • 5+ years (Developer) / 6-10 years (Lead) of Data Engineering experience.
  • Strong hands-on experience with Google Cloud Platform (Google Cloud Platform).
  • Expertise in BigQuery for data warehousing and analytics.
  • Experience developing and maintaining workflows using Apache Airflow.
  • Advanced SQL skills for complex queries and performance optimization.
  • Hands-on experience with DBT (Data Build Tool) for data transformation.
  • Experience building scalable ETL/ELT pipelines.
  • Knowledge of data modeling, data warehousing, and dimensional modeling.
  • Experience with Git and CI/CD practices.
  • Strong debugging, optimization, and performance tuning skills.

< data-start=1310 data-end=1331>Preferred Skills

  • Python for data engineering and automation.
  • Experience with Cloud Composer, Cloud Storage, Pub/Sub, or Dataflow.
  • Familiarity with Agile/Scrum methodologies.
  • Excellent communication and collaboration skills.

Apply for this position

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

Apply on www.dice.com

Good distractions

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

2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon · WWC Europe 2026

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

3:27 min

Explaining query execution overhead and caching limitations in BigQuery

Adnan Rahic · JS Congress

2:57 min

Core technical practices for robust data engineering

Sandhya Menon Sandhya Menon · WWC Europe 2026

56 sec

Favorite git commands and the importance of patch commits

Eileen Uchitelle Eileen Uchitelle +1 · Coffee With Developers

3:05 min

Audience questions on AI agents and pipeline vectorization

Joy Joy · WWC 2024

Videos

See all

Related articles

See all