WeAreDevelopers Logo WeAreDevelopers
Sign in
For You LIVE
Back

Lead Cloud Data & AI Engineer / Solutions Architect (Google Cloud Platform)

Talent Vista Inc.
Reston, VA, United States
5 days ago
Apply on www.dice.com
Prepare application

Role details

Contract type
Permanent contract
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

Artificial Intelligence Airflow BigQuery Cloud Computing Databases Distributed Data Store Data Flow Control Identity and Access Management Python (Programming Language) PostgreSQL Machine Learning Oracle (Applications)
+11 more
Performance Tuning Tensorflow Cloudera Google Cloud Pytorch Large Language Models Apache Spark Pyspark Machine Learning Operations Serverless Computing Apache Beam

Requirements

  • Expert-level Google Cloud Platform Data Stack: BigQuery (Dremel, IAM, architecture), Dataflow (Apache Beam), Dataproc (Serverless Spark / PySpark), Cloud Composer (Airflow), Pub/Sub, and dbt.
  • 10+ years in relational/distributed databases (PostgreSQL, AlloyDB, Oracle, CloudSQL) with performance tuning, replication, and migration experience.

  1. Applied AI & MLOps: * Experience developing, deploying, and operationalizing ML models & LLM pipelines (Python, PyTorch, TensorFlow, MLOps tooling).

  2. Public Sector / Security Standards: * Familiarity with US Public Sector data compliance (e.g., DoD IL5/IL6 environments). * Excellent stakeholder-facing advisory, architecture consulting, and workshop delivery skills.

  3. Preferred Credentials: * Google Cloud Platform Professional Certifications (Data Engineer, ML Engineer, Cloud Architect, Database Engineer).

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

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · World Congress 2023

2:19 min

Introduction to Apache Airflow for advanced orchestration

Alan Mazankiewicz · LIVE

4:32 min

Harnessing Spark with Python using PySpark and Py4J

Ayon Roy · LIVE

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

1:06 min

Compiling PyTorch environments for advanced time forecasting

Christoph Lohrmann Christoph Lohrmann +1 · World Congress 2026 Europe

1:44 min

Career transition into cloud native and data management

Michael Cade · LIVE

Videos

See all
The Cloud is Calling: Answer with In-Demand Skills thumbnail
21:23
World Congress 2024 • about 2 years ago

The Cloud is Calling: Answer with In-Demand Skills

Asrar

PySpark - Combining Machine Learning & Big Data thumbnail
43:26
LIVE • almost 6 years ago

PySpark - Combining Machine Learning & Big Data

Ayon Roy

Fully Orchestrating Databricks from Airflow thumbnail
39:14
LIVE • almost 5 years ago

Fully Orchestrating Databricks from Airflow

Alan Mazankiewicz

Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding) thumbnail
29:32
World Congress 2026 Europe • 3 months ago

Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)

Christoph Lohrmann, Utz Bacher

Data Science in Retail thumbnail
58:21
LIVE • over 3 years ago

Data Science in Retail

Julian Joseph

From Messy Queries to Scalable Systems - How Data Engineering actually works thumbnail
31:15
World Congress 2026 Europe • 3 months ago

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

Sandhya Menon

Related articles

See all