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Remote Data Engineering Apprenticeship Jobs in Arizona

Koantek

Databricks Platform Architect

Chandler, AZ · Remote

Lead Data Platform Architect / Data bricks Migration Lead Location: Remote Position Type: Contract ... Pipeline Engineering: Design distributed processing frameworks, control flows, and configuration ...

YO AI Labs

SWE AI Training Data Expert - Remote

Phoenix, AZ · Remote

$80 - $120/hr

Senior Software Engineer Job Type: Contractor (~15 hours/week) Location: Remote Job Summary We are ... Strong understanding of algorithms and data structures . * Experience with bug fixing and debugging ...

Koantek

Resource Manager

Chandler, AZ · Remote

Remote (Coverage for EST & PST required) Role Overview As the Resource Manager for Koantek ... Familiarity with the Databricks ecosystem or similar data engineering platforms.

Achieve

Sr. Data Analyst

Tempe, AZ · On-site +1

Coursework in Statistical Programming, Simulation, Regression * Knowledge of and ability to ... Hybrid and remote work opportunities * Medical, dental, and vision with HSA and FSA options Note:

Achieve

Sr. Data Analyst

Tempe, AZ · On-site +1

$115K - $145K/yr

Coursework in Statistical Programming, Simulation, Regression * Knowledge of and ability to ... Hybrid and remote work opportunities * Medical, dental, and vision with HSA and FSA options Note:

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Remote Data Engineering Apprenticeship information

What is a remote data engineering apprenticeship?

A Remote Data Engineering Apprenticeship is a structured training program where individuals learn the fundamentals of data engineering while working remotely. Apprentices typically gain hands-on experience with data pipelines, databases, and tools such as SQL, Python, and cloud services under the supervision of experienced mentors. The goal is to prepare apprentices for a full-time role as a data engineer by exposing them to real-world projects and industry best practices. This type of apprenticeship is ideal for those looking to start a career in data engineering while benefiting from the flexibility of remote work.

What skills and qualifications are needed to thrive as a remote data engineering apprentice?

To excel as a Remote Data Engineering Apprentice, you need a foundational understanding of programming (especially Python or SQL), data modeling, and database management, typically supported by relevant coursework or a degree in computer science or a related field. Familiarity with cloud platforms (like AWS or Google Cloud), ETL tools, and version control systems (such as Git) is often required, and certifications in these areas can be beneficial. Strong problem-solving, communication, and self-motivation are vital soft skills for collaborating virtually and adapting to new challenges. These skills ensure you can effectively contribute to data projects, learn quickly in a remote environment, and support team goals in a rapidly evolving field.

What are common challenges faced by remote data engineering apprentices, and how can they be managed?

Remote data engineering apprentices often encounter challenges such as limited face-to-face mentorship, managing time zones, and ensuring strong communication with team members. To overcome these, it helps to proactively schedule regular check-ins with mentors, set clear daily goals, and utilize collaboration tools like Slack or Jira. Establishing a dedicated workspace and adhering to a structured routine can also foster productivity and help apprentices stay engaged with their projects and team.

What is the difference between Remote Data Engineering Apprenticeship vs Remote Data Engineer?

AspectRemote Data Engineering ApprenticeshipRemote Data Engineer
Required CredentialsTypically entry-level, often requiring basic programming or data fundamentalsUsually requires a bachelor's degree in computer science, data science, or related field, with experience in data tools
Work EnvironmentTraining-focused, often part-time or structured learning programsFull-time remote role with project responsibilities
Employer & Industry UsageUsed by companies to train new talent; common in tech and data-driven industriesHired as a professional to develop and maintain data pipelines and systems

The Remote Data Engineering Apprenticeship is an entry-level training program designed to develop foundational skills in data engineering, often with mentorship and structured learning. In contrast, a Remote Data Engineer is a full-time professional responsible for building and managing data infrastructure. The apprenticeship prepares individuals for a career in data engineering, while the data engineer role involves applying those skills in real-world projects.

What are the most commonly searched types of Data Engineering Apprenticeship jobs in Arizona?

The most popular types of Data Engineering Apprenticeship jobs in Arizona are:

What are popular job titles related to Remote Data Engineering Apprenticeship jobs in Arizona?

For Remote Data Engineering Apprenticeship jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Remote Data Engineering Apprenticeship jobs in Arizona look for?

The top searched job categories for Remote Data Engineering Apprenticeship jobs in Arizona are:

What cities in Arizona are hiring for Remote Data Engineering Apprenticeship jobs?

Cities in Arizona with the most Remote Data Engineering Apprenticeship job openings:

Remote Data Engineering Apprenticeship jobs near you
Infographic showing various Remote Data Engineering Apprenticeship job openings in Arizona as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Databricks Platform Architect

Koantek

Chandler, AZ • Remote

Contractor

Re-posted 25 days ago

Job description

Job Title: Lead Data Platform Architect / Data bricks Migration Lead Location: Remote Position Type: Contract Job Overview We are seeking an accomplished, technology-driven Lead Data Platform Architect / Migration Specialist to spearhead the modernization of our core enterprise financial and tax allocation engines. In this role, you will lead the architectural design, definition of migration strategies, and hands-on implementation to transition large-scale legacy relational database systems (SQL Server/T-SQL) into a modern, cloud-native Databricks Lakehouse platform. The ideal candidate will have extensive experience in high-throughput distributed systems, Databricks compute optimization, performance tuning, and complex pipeline orchestration.

Key Responsibilities Architecture & Strategy: Validate, refine, and own the target architecture on Databricks. Define robust migration strategies and production-ready reference patterns to convert 150+ complex stored procedures into PySpark and Structured/Declarative Pipelines (SDP). Pipeline Engineering: Design distributed processing frameworks, control flows, and configuration-driven parameter handling for both full and incremental recalculation modes.

Performance Optimization: Address performance deltas between small and large workloads. Architect and implement acceleration techniques such as caching, partition pruning, cluster sizing, and offline/pre-calculation strategies to maintain sub-30-second user-facing reporting SLAs. Orchestration & Observability: Design and deploy enterprise-level pipeline orchestration using tools like Apache Airflow or Databricks Workflows.

Integrate robust logging, error handling, and observability patterns into existing enterprise monitoring frameworks. Governance & Security: Implement data governance models, data lineage, and schema evolution utilizing tools like Unity Catalog. AI-Assisted Delivery & Code Quality: Establish best practices for AI-assisted code generation (e.g., using Claude or advanced LLMs), providing code-review patterns and refactoring frameworks to ensure maintainable and performant output

Team Enablement: Lead code walkthroughs, design reviews, and pair-programming sessions with the development team to accelerate knowledge transfer and technical excellence. Required Technical Skills & Qualifications Core Big Data Platform: Deep expert-level knowledge of Databricks (Lakehouse architecture, Delta Lake, Unity Catalog) and Apache Spark / PySpark. Legacy Database Expertise: Strong background in relational databases, with advanced proficiency in SQL Server, T-SQL, and Stored Procedures.

Ability to reverse-engineer and refactor legacy database logic into distributed paradigms. Orchestration Tools: Hands-on experience with Apache Airflow or similar modern workflow orchestrators. Performance Tuning: Proven track record in cost optimization (FinOps), cluster tuning, autoscaling configurations, and handling skewed data profiles.

CI/CD & DevOps: Experience with Infrastructure as Code (Terraform), data build tool (dbt), testing frameworks (PyTest), and automated Git-based workflows. Experience Level: 10+ years of experience in Data Engineering/Architecture, with at least 3+ years specifically leading large-scale cloud data migrations. Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

Preferred Certifications Databricks Certified Data Engineer Associate / Professional Databricks Certified Solutions Architect AWS Certified Database Specialist or equivalent Cloud Certifications

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