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Overnight Databricks Data Engineer Jobs in Arizona

Stellar IT Group

Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Data Engineer Location: Phoenix, AZ(Hybrid) Job Type: FTE Key Responsibilities Data Platform ... Design, develop, and maintain cloud-native data pipelines using Databricks, Microsoft Azure Data ...

Forhyre

Data Engineer

Phoenix, AZ

$113K - $136K/yr

Databricks Nice to have: Informatica/ETL. Responsibilities * Design and develop ETL processes based ... Proven working experience as a data engineer * Bachelor degree or equivalent in Computer Science

RIT Solutions, Inc.

AWS data engineer

Chandler, AZ · On-site

$63.50 - $83.50/hr

Responsibilities : • Must have: aws data, datazone, databricks, glue or spark, python, data warehousing, CI/CD • Bachelor's degree in Computer Science, Engineering or related field • 5+ years ...

Smart Synergies

Data Engineering Lead

Glendale, AZ · On-site

The ideal candidate will possess deep architectural knowledge of Azure Data Lake and Databricks, a ... Azure certifications, such as Azure Data Engineer Associate or Azure Solutions Architect Expert.

Koantek

Databricks Platform Architect

Chandler, AZ · Remote

CI/CD & DevOps: Experience with Infrastructure as Code (Terraform), data build tool (dbt), testing ... Preferred Certifications Databricks Certified Data Engineer Associate / Professional Databricks ...

Pwc

GenAI Python Systems Engineer-Manager

Phoenix, AZ · On-site

$99K - $232K/yr

Azure Solutions Architect Expert, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Proficient in Python and SQL - Experience with Docker and ...

Insight

Principal Data Scientist

Phoenix, AZ · On-site +1

Build and guide ML solutions on Databricks, using notebooks, feature engineering, MLflow, Delta Lake, and scalable data pipelines to support healthcare AI and analytics use cases. * End-to-End ML ...

Arrivia

Fabric Data Engineer

Scottsdale, AZ · Hybrid

$115K - $138K/yr

... Databricks. * Experience with real-time and streaming data at scale, including event-driven ... Fabric Data Engineer Associate (DP-700) is highly preferred. * A bachelor's degree in a related ...

Arrivia

Fabric Data Engineer

Scottsdale, AZ · On-site

$115K - $138K/yr

... Databricks. * Experience with real-time and streaming data at scale, including event-driven ... Fabric Data Engineer Associate (DP-700) is highly preferred. * A bachelor's degree in a related ...

RIT Solutions, Inc.

AWS data engineer

Chandler, AZ · On-site

RIT Solutions, Inc. is seeking an AWS Data Engineer to join their team in Chandler, AZ. The role ... DataBricks • Glue, Spark, ETL • Python • CI/CD pipelines • Understanding of data warehouse ...

Pwc

Data Engineer - Senior Associate

Phoenix, AZ · On-site

$77K - $202K/yr

... Engineer - Senior Associate, you will focus on designing and building data infrastructure and ... Databricks Unified Data Analytics Platform for advanced data analytics and visualization ...

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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

Data Engineer

Stellar IT Group

Phoenix, AZ • On-site

$113K - $136K/yr

Full-time

Re-posted 25 days ago

Job description

Overview:
Job Title: Data Engineer
Location: Phoenix, AZ(Hybrid)
Job Type: FTE
Key Responsibilities
Data Platform & Pipeline Development
  • Design, develop, and maintain cloud-native data pipelines using Databricks, Microsoft Azure Data Factory, and Microsoft Fabric to support data integration and analytics solutions.
  • Implement incremental and real-time data ingestion strategies using a medallion architecture for data lake storage.
  • Write, optimize, and maintain complex SQL queries to transform, integrate, and analyze data across enterprise systems.
  • Develop solutions with a focus on scalability, maintainability, testability, and long-term operability within a continuous delivery mindset.

Data Operations & Reliability
  • Support and troubleshoot legacy data platforms built on SSIS and SQL Server, ensuring high availability and performance of critical data processes.
  • Identify, troubleshoot, and resolve data integration and data quality issues to ensure reliable production data delivery.
  • Contribute to observability, automated validation, and CI/CD pipelines to support fast feedback and safe releases.

Agile Collaboration & Engineering Practices
  • Collaborate daily with product owners, QA, and engineers through Scrum ceremonies including standups, backlog refinement, sprint planning, sprint reviews, and retrospectives.
  • Participate in proof-of-concept efforts, technical spikes, and design discussions, providing thoughtful technical analysis and pragmatic recommendations.
  • Apply XP engineering practices such as pairing, incremental delivery, continuous refactoring, and shared code ownership to maintain high-quality, evolvable systems.
  • Clearly communicate technical concepts, risks, tradeoffs, and progress to both technical and non-technical stakeholders.

Requirements
Required Qualifications
  • 5+ years of experience designing and building data solutions.
  • Strong proficiency in SQL and Python for data analytics and transformation.
  • Hands-on experience with ETL pipeline development and automation.
  • Solid understanding of data lake architecture and design principles.
  • Experience working on Agile teams (Scrum, XP, or similar), with regular participation in standups, sprint planning, refinement, reviews, and retrospectives.
  • Comfort operating in highly collaborative environments with frequent verbal and written communication across engineering, product, and QA teams.
  • Ability to break work into small, iterative deliverables and adapt quickly based on feedback and changing priorities.
  • Strong ownership mindset, including accountability for the quality, reliability, and maintainability of delivered solutions.

Preferred Qualifications
  • Experience with Azure cloud services and cloud-based ETL tools.
  • Familiarity with data visualization tools such as Power BI or Tableau.
  • Understanding of event-driven architectures, including queues, batch processing, and pub/sub models.
  • Exposure to NoSQL databases such as MongoDB or Cassandra.
  • Experience working on product engineering teams delivering customer-facing or operationally critical systems.
  • Familiarity with modern engineering practices inspired by XP, including automated testing, pairing, refactoring, and continuous integration.
  • Experience operating systems in production environments with uptime, reliability, and observability expectations.

Bonus Points For
  • Experience in Data Science or Machine Learning, particularly in model deployment or feature engineering.
  • Experience contributing to engineering standards, documentation, or continuous improvement initiatives within an Agile team.

Skills:
SQL,Python

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