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2 jobs found

Today

Google Cloud AI Engineer

Altimetrik Corp Remote 🌍 Remote

Remote

Today

Full time Artificial Intelligence Big Data Bigquery

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Job Description

Altimetrik Corp is hiring a Google Cloud AI Engineer (Remote) to design and deploy AI agents grounded in unique business data within Google’s Data Cloud for the agentic era.

Responsibilities

Develop intelligent agents using Vertex AI Agent Builder to automate complex business workflows
Use Agent Developer Kit (ADK) to build and manage multi-agent systems for end-to-end business problem solving
Connect agents to enterprise databases securely using tools such as MCP (Model Context Protocol) Toolbox with BigQuery and Spanner
Train, tune, and deploy models with Vertex AI, integrating with BigQuery for feature engineering
Build and optimize streaming data pipelines (for example, Dataflow) to run real-time inference via RunInference API or Vertex AI endpoints
Ground AI models in live business context using vector engines in BigQuery or AlloyDB to reduce “AI amnesia”
Attend internal and client-facing meetings promptly
Send regular, structured status updates on project milestones and technical blockers
Ask for help when encountering technical hurdles and support collaborative troubleshooting
Translate high-level business goals into robust technical architectures while navigating corporate environments

Requirements

Proven experience with Model Garden, Vertex AI Pipelines, and model evaluation
Advanced SQL skills for BigQuery
Advanced Python for ML engineering and data preprocessing (scaling, encoding, imputation)
Hands-on experience with Google Cloud Storage and Vertex AI endpoints
Familiarity with stateful real-time processing and current innovations in agentic architectures

Technologies

Vertex AI Agent Builder
Agent Developer Kit (ADK)
MCP (Model Context Protocol) Toolbox
BigQuery
Spanner
Vertex AI
Dataflow
RunInference API
AlloyDB
SQL
Python
Google Cloud Storage
Model Garden
Vertex AI Pipelines

Preferred Experience

Experience in financial services or retail to support industry-specific data logic (credit risk, royalty forecasting, search relevance)
Knowledge of privacy and compliance standards for handling PII via masking and redaction

Benefits

401(k)
Health insurance

Application

Willingness to complete a pre-employment background check contingent upon an offer

Travel

25% travel (required)

Work Location: Remote

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2d ago

GCP BigQuery Data Engineer

Virtues Irving, TX

Irving, TX

2d ago

$100k - $110k/yr Full time Analytics Big Data Bigdata

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Job Description

Virtues is seeking a GCP BigQuery Data Engineer to design cloud-native, scalable data platforms and build real-time ingestion pipelines on Google Cloud. This onsite role in Irving, TX focuses on event-driven streaming architectures that support near real-time analytics and enterprise reporting.

Responsibilities

Design, develop, and optimize enterprise data warehouse solutions using Google BigQuery.
Design, develop, and maintain real-time data ingestion pipelines using Apache NiFi to extract, transform, and route streaming data into Apache Kafka topics.
Build scalable event-driven streaming architectures using Apache NiFi, Apache Kafka, and Google BigQuery to enable high-throughput, fault-tolerant, low-latency processing.
Configure and optimize Apache NiFi processors for extraction, transformation, routing, filtering, schema validation, error handling, retry mechanisms, and reliable delivery to Kafka.
Develop streaming ingestion solutions that allow Google BigQuery to consume Kafka event streams and transform near real-time events into analytical tables and reporting datasets.
Design data models and implement ETL/ELT processes to move data from raw to curated and published layers.
Design, create, and manage large-scale BigQuery datasets, including temporary/permanent and internal/external tables.
Optimize BigQuery workloads using query tuning, partitioning, clustering, and cost optimization techniques to improve performance and reduce cloud costs.
Monitor, troubleshoot, and optimize streaming workloads by tuning NiFi flows, Kafka topics/partitions, and BigQuery streaming ingestion to support high availability, data integrity, minimal latency, and cost-efficient processing.
Build scalable data lake frameworks and ingestion pipelines using cloud-native GCP technologies.
Develop reporting and visualization solutions using Looker, Looker Studio (Data Studio), Connected Sheets, and other BigQuery reporting tools.
Collaborate with data architects, modelers, developers, DevOps engineers, project managers, and business stakeholders to deliver scalable enterprise analytics solutions and continuous improvements to the data platform.

Requirements

7+ years of experience in Data Engineering, Data Warehousing, or Big Data platforms.
Must-have skills: Apache NiFi and Apache Kafka.
Strong hands-on experience with Google Cloud Platform (GCP), including BigQuery, Cloud Dataflow, Pub/Sub, and Google Cloud Storage (GCS).
Hands-on experience designing and supporting real-time streaming pipelines using Apache NiFi, Apache Kafka, and Google BigQuery.
Experience using BigQuery Console/Query Editor for data management, performance tuning, and SQL development.
Strong experience designing scalable data models, ETL/ELT pipelines, data lake architectures, and enterprise data warehouse solutions.
Experience with batch and streaming data ingestion using GCP services.
Thorough understanding of BigQuery cost structure, including storage, ingestion, and query costs, with experience implementing query optimization, partitioning, clustering, and other cost optimization techniques.
Experience managing large-scale datasets, including temporary/permanent and internal/external BigQuery tables.
Experience developing reporting and visualization solutions using Looker, Looker Studio (Data Studio), and Connected Sheets.
Excellent verbal and written communication skills, with the ability to collaborate with technical teams, business stakeholders, senior management, and executive leadership.
Experience working in Agile environments and collaborating with cross-functional teams to deliver enterprise data engineering solutions.

Preferred Qualifications

Google Cloud certifications.
Experience delivering enterprise-scale analytics and cloud data solutions.

Technologies

Google BigQuery
Apache NiFi
Apache Kafka
Google Cloud Dataflow
Google Pub/Sub
SQL
ETL/ELT
Google Cloud Storage (GCS)
Looker
Looker Studio (Data Studio)
Connected Sheets
CI/CD
DevOps
Agile/Scrum
Python
Spark
Data Modeling
Data Warehousing
Data Lakes
Batch & Streaming Pipelines

Compensation and Location

Salary: USD 100,000 - 110,000 per year.

Work location: In person (Irving, TX).

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