GCP BigQuery Data Engineer
Analytics
Big Data
Bigdata
Bigquery
Business Intelligence
CI/CD
Cloud
Cloud Platform
Data
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Integration
Data Lake
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Visualization
Data Warehouse
Database
Databases
Dataviz
DevOps
Digital Marketing
ETL
Google Cloud Dataflow
Google Cloud Storage
Google Pub/sub
Informatica
Kafka
Looker
Nifi
Reporting and Analytics
Software Development
Spark
SQL
Stream Processing
Streaming Data
Visual Design
Job Description
Build cloud-native, scalable analytics and near-real-time ingestion pipelines across GCP BigQuery and event-driven streaming systems.
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 capture, transform, and route streaming data into Apache Kafka topics.
- Build event-driven streaming architectures across Apache NiFi, Apache Kafka, and Google BigQuery for high-throughput, fault-tolerant, low-latency processing.
- Configure and optimize Apache NiFi processors for extraction, transformation, routing, filtering, schema validation, error handling, retries, and reliable delivery to Kafka.
- Develop streaming ingestion solutions enabling Google BigQuery to consume Kafka event streams and transform data into analytical tables and enterprise reporting datasets.
- Design data models and implement ETL/ELT processes to move data from raw to curated and published layers.
- Create and manage large-scale BigQuery datasets, including temporary/permanent and internal/external tables.
- Optimize BigQuery workloads through query tuning, partitioning, clustering, and cost optimization techniques.
- 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 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 and continuous data platform improvements.
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 ingestion using GCP services.
- Thorough understanding of BigQuery cost structure (storage, ingestion, and query costs) and 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, able to collaborate effectively 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.
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
- DevOps
- CI/CD
- Agile/Scrum
- Python
- Spark
- Data Modeling
- Data Warehousing
- Data Lakes
- Batch & Streaming Pipelines
Preferred Qualifications
- Google Cloud certifications.
- Experience delivering enterprise-scale analytics and cloud data solutions.
Pay
$100,000.00 - $110,000.00 per year
Work Location
- Onsite in Irving, TX