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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

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