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Data Platform Engineer

EITAcies, Inc.
Phoenix, AZ, United States
5 days ago
Apply on www.juju.com
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Role details

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

Tech stack

Airflow BigQuery Cloud Storage Data as a Services Directed Acyclic Graph (Directed Graphs) Data Validation Information Engineering Data Infrastructure Python (Programming Language) Operational Databases Standard Sql Cloudera
+8 more
SQL Databases Google Cloud Apache Spark Fastapi Pyspark Api Design Restful APIs Data Pipelines

Job description

We are hiring a Senior Data Platform Engineer for an onsite role in Phoenix, AZ. This role requires strong hands-on experience building and operating data pipelines on Google Cloud Platform., * Design and maintain Airflow DAGs for production data workflows

  • Develop and optimize Spark / PySpark jobs on Dataproc
  • Build and optimize complex SQL transformations
  • Develop REST APIs using FastAPI Python to support data services
  • Implement robust data quality and validation frameworks
  • Monitor pipeline performance, retries, and SLA compliance

Requirements

  • 6+ years of data engineering experience
  • Strong Python programming skills
  • Production experience with Apache Spark PySpark
  • Experience with Airflow DAG development
  • Hands-on experience with GCP (Dataproc, BigQuery, Cloud Storage preferred)
  • Experience building APIs using FastAPI
  • Strong SQL and data modeling knowledge
  • Experience implementing data quality checks (schema validation, row count checks, anomaly detection)

Benefits & conditions

  • 401(k)

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.juju.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

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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

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Key features and advantages of using FastAPI

Ashmi Banerjee · World Congress 2022

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Maria Apazoglou · Coffee With Developers

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Deploying and running Airflow in cloud environments

Alan Mazankiewicz · LIVE

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Core technical practices for robust data engineering

Sandhya Menon Sandhya Menon · World Congress 2026 Europe

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World Congress 2026 Europe • 3 months ago

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LIVE • almost 5 years ago

Fully Orchestrating Databricks from Airflow

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PySpark - Combining Machine Learning & Big Data

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World Congress 2022 • over 4 years ago

Build your backend using FastAPI

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LIVE • over 3 years ago

Data Science in Retail

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