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Overnight Databricks Data Engineer Jobs in Arizona

Phoenix Staff

Mid-Senior Data Engineer

Phoenix, AZ · Hybrid

$100K - $115K/yr

Job Title: Data Engineer (Mid-Level to Senior) Location: Hybrid / Onsite as needed (project ... Exposure to analytics or data science tools (Databricks, Azure ML, etc.). * Understanding of data ...

Globe Telecom, Inc.

Data Modeler

Globe, AZ

$52 - $67.50/hr

Certifications related to Cloud Data Architecture (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer, or Databricks Certified Data Engineer) is a plus. Equal Opportunity ...

Confiz Limited

Principal AI Engineer

Phoenix, AZ · On-site

$180 - $230/hr

Define data architecture and pipelines using Databricks (Delta Lake, Unity Catalog, MLflow) for ... Collaborate with data engineers, ML engineers, full-stack developers, and product owners to ...

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Overnight Databricks Data Engineer information

What is the difference between Overnight Databricks Data Engineer vs Data Engineer?

AspectOvernight Databricks Data Engineer
Work EnvironmentPrimarily remote or on-site, working overnight shifts to support global data operations
CertificationsDatabricks certifications, cloud platform credentials (AWS, Azure), data engineering certifications
Tools & TechnologiesDatabricks platform, Spark, cloud services, SQL, Python, ETL tools
Industry UsageTech, finance, healthcare, retail with 24/7 data needs

While both roles focus on data engineering, the Overnight Databricks Data Engineer specializes in managing data pipelines on the Databricks platform during overnight shifts, often supporting global operations. A Data Engineer may work across various platforms and shifts, with broader responsibilities in data architecture and pipeline development. The overnight role emphasizes specific platform expertise and shift timing, catering to organizations with continuous data processing needs.

What unique challenges do overnight Databricks data engineers face, and how can they be addressed?

Overnight Databricks Data Engineers often work with limited real-time support, which can present challenges when troubleshooting urgent data pipeline issues or system outages. To address this, it’s essential to develop strong problem-solving skills, document processes thoroughly, and leverage automated monitoring and alerting tools. Additionally, close collaboration with daytime teams during handoff periods ensures continuity and minimizes disruptions. Building a habit of proactive communication and maintaining detailed logs helps the entire team resolve issues efficiently and maintain data quality.

What skills and qualifications are needed to thrive as an overnight Databricks data engineer?

To thrive as an Overnight Databricks Data Engineer, you need strong proficiency in data engineering, Python or Scala programming, and experience with big data technologies, typically supported by a relevant degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (such as AWS or Azure), and certifications like Databricks Certified Data Engineer are highly valued. Attention to detail, problem-solving, and effective communication are essential soft skills, especially for troubleshooting and collaborating across shifts. These competencies ensure reliable data pipeline management and efficient resolution of issues during off-hours, maintaining seamless business operations.

What is an overnight Databricks data engineer?

An Overnight Databricks Data Engineer is a professional who works primarily during night shifts to manage, design, and maintain big data pipelines and workflows using Databricks, a cloud-based data analytics platform. Their responsibilities often include developing and optimizing data processing jobs, ensuring data quality, and troubleshooting issues that arise during overnight data operations. This role is critical for organizations that require 24/7 data processing, continuous ETL jobs, or real-time analytics. Working overnight may also involve monitoring automated systems, performing scheduled data loads, and collaborating with global teams to ensure data availability and reliability.

What are the most commonly searched types of Databricks Data Engineer jobs in Arizona?

The most popular types of Databricks Data Engineer jobs in Arizona are:

What cities in Arizona are hiring for Overnight Databricks Data Engineer jobs?

Cities in Arizona with the most Overnight Databricks Data Engineer job openings:

Overnight Databricks Data Engineer jobs near you

Mid-Senior Data Engineer

Phoenix Staff

Phoenix, AZ • Hybrid

$100K - $115K/yr

Full-time

Re-posted 10 days ago

Job description

Job Title: Data Engineer (Mid-Level to Senior)

Location: Hybrid / Onsite as needed (project-dependent)

Salary: $100,000 - $115,000


We are partnering with an organization seeking a skilled Data Engineer to support the design, build, and optimization of a modern data platform. This role focuses on developing scalable data pipelines and infrastructure that power analytics, reporting, and AI initiatives. The ideal candidate is comfortable working across Fabric and the modern Microsoft data stack (e.g., Azure Data Factory, Azure Data Lake Storage, Azure SQL Database / Managed Instance, Cosmos DB, etc.) and enjoys solving complex data transformation and integration challenges in a collaborative environment.


Your role:

  • Design, build, and maintain ETL/ELT pipelines using Azure Data Factory and related tools.
  • Architect and manage data lake and data warehouse solutions.
  • Transform and move data across relational, NoSQL, and object storage systems.
  • Collaborate with engineering and product teams to define data requirements and solutions.
  • Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
  • Ensure data quality and integrity across systems.
  • Document data flows, schemas, and architecture decisions.
  • Contribute to data platform strategy and ongoing improvements.


What you’ve got:

  • 3+ years of experience for mid-level candidates; 6+ years for senior-level candidates.
  • Strong experience with Azure Data Factory or similar ETL/ELT tools.
  • Solid understanding of database design (relational modeling, normalization/denormalization).
  • Experience with data lakes and/or data warehouses (Azure Data Lake, Microsoft Fabric, etc.).
  • Experience transforming structured, semi-structured, and unstructured data.
  • Proficiency in SQL and experience with Azure SQL Database and/or Azure SQL Managed Instance.
  • Familiarity with Azure data services and the Microsoft data ecosystem.
  • Strong problem-solving skills and ability to work both independently and collaboratively.


Preferred:

  • Experience with Cosmos DB or other NoSQL platforms.
  • Knowledge of KQL and Azure Monitor / Data Explorer.
  • Experience with object storage and file-based data architectures.
  • Exposure to analytics or data science tools (Databricks, Azure ML, etc.).
  • Understanding of data governance, lineage, and cataloging best practices.


To find more great tech-centric jobs, please visit www.phoenixstaff.com