WeAreDevelopers Logo WeAreDevelopers
Sign in
For You LIVE
Back

Lead Google Cloud Platform Data Engineer - Remote / Telecommute

CYNET SYSTEMS INC.
Dallas, TX, United States
26 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
1 year minimum
Working hours
Regular working hours
Job source
www.dice.com

Tech stack

Airflow BigQuery Information Engineering Extract Transform Load (ETL) Data Flow Control Query Optimization SQL Databases Unstructured Data Google Cloud Cerner CCL Data Pipelines

Job description

  • Design and implement scalable data pipelines using Google Cloud Platform services (BigQuery, Dataflow, Cloud Composer, Pub/Sub).
  • Develop and optimize data models and schemas in BigQuery for high-performance analytics.
  • Build and maintain ETL/ELT pipelines for ingesting structured and unstructured data.
  • Implement data partitioning, clustering, and query optimization strategies in BigQuery.

Requirements

  • 1+ years of experience in data engineering and development.
  • Strong expertise in Google Cloud Platform (Google Cloud Platform) services, particularly BigQuery.
  • Experience in building and maintaining ETL/ELT pipelines for structured and unstructured data.
  • Ability to interpret and convert SQL and CCL scripts into BigQuery.

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.

Moments

Explore playlists

2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon · WWC Europe 2026

2:30 min

Leveraging BigQuery ML for scalable SQL-based segmentation experiments

Julian Joseph · LIVE

2:14 min

Solving complex platform architecture challenges at an enterprise scale

Maria Apazoglou · Coffee With Developers

3:05 min

Audience questions on AI agents and pipeline vectorization

Joy Joy · WWC 2024

3:27 min

Explaining query execution overhead and caching limitations in BigQuery

Adnan Rahic · JS Congress

1:44 min

Career transition into cloud native and data management

Michael Cade · LIVE

Videos

See all
Data Science in Retail thumbnail
58:21
LIVE • about 3 years ago

Data Science in Retail

Julian Joseph

From Messy Queries to Scalable Systems - How Data Engineering actually works thumbnail
31:15
WWC Europe 2026 • about 1 month ago

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

Sandhya Menon

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

Enjoying SQL data pipelines with dbt

Matthias Niehoff

Making Data Warehouses fast. A developer's story. thumbnail
42:16
JS Congress • over 4 years ago

Making Data Warehouses fast. A developer's story.

Adnan Rahic

Data Governance in the Era of AI thumbnail
20:04
WWC 2025 • 12 months ago

Data Governance in the Era of AI

Kateřina Ščavnická

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

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

Joy

Related articles

See all