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Remote Data Engineering Apprenticeship Jobs (NOW HIRING)

Courier Newsroom, Inc.

Data Engineering Director

NY · Remote

DATA ENGINEERING DIRECTOR Remote (U.S.-based) | Full-Time | $130K-$140K Join Courier Newsroom - an organization that drives journalism and empowers communities. AtCourier Newsroom, we're reinventing ...

NAVA Software Solutions

Data Engineer - Remote

Manhattan, NY · On-site +1

$126K - $151K/yr

Remote Seeking a highly skilled and motivated Data Engineer to join a dynamic team. As a key ... Perform data engineering and analytics tasks, including data ingestion, SQL orchestration, and data ...

Jobgether

You will have the autonomy to influence technology choices and establish best practices in a remote-first culture. Accountabilities: As the Head of Data Engineering, you will own the strategy ...

DivIHN

Senior Data Developer (Remote)

Remote Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be ... Required Qualifications * 7+ years of experience in data engineering, ETL development, or cloud ...

Salas O'Brien

Director, Data Engineering & Architecture

$175K - $200K/yr

Director, Data Engineering & Architecture Salas O'Brien | Digital & AI Reports To: SVP, Digital ... Remote (United States) Travel: Up to 20% Compensation: $175,000- $200,000 base salary, eligible for ...

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Remote Data Engineering Apprenticeship information

What are the key skills and qualifications needed to thrive as a Remote Data Engineering Apprentice, and why are they important?

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 some common challenges faced by remote data engineering apprentices, and how can they be effectively 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 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 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.

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Remote Data Engineering Apprenticeship jobs near you
Infographic showing various Remote Data Engineering Apprenticeship job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 83% Full Time, 11% Part Time, 1% Contract, and 3% Nights. Highlights an 99% Physical, and 1% Remote job distribution.
Manager, Data Engineering - Archimedes

Manager, Data Engineering - Archimedes

Navitus Health Solutions, LLC

Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 27 days ago

Job description

Company
Archimedes
About Us
Archimedes - Transforming the Specialty Drug Benefit - Archimedes is the industry leader in specialty drug management solutions. Founded with the goal of transforming the PBM industry to provide the necessary ingredients for the sustainability of the prescription drug benefit - alignment, value and transparency - Archimedes achieves superior results for clients by eliminating tightly held PBM conflicts of interest including drug spread, rebate retention and pharmacy ownership and delivering the most rigorous clinical management at the lowest net cost. .. Current associates must use SSO login option at https://employees-navitus.icims.com/ to be considered for internal opportunities.We are committed to providing equal employment opportunity to all applicants and employees and comply with all applicable nondiscrimination regulations, including those related to protected veterans and individuals with disabilities. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, or handicap.
Pay Range
USD $0.00 - USD $0.00 /Yr.
STAR Bonus % (At Risk Maximum)
0.00 - Ineligible
Work Schedule Description (e.g. M-F 8am to 5pm)
Core Business Hours- Remote or Hybrid 3 Days in Office from our St. Louis, MO or Brentwood, TN offices
Remote Work Notification
ATTENTION: Archimedes is unable to offer remote work to residents of Alaska, Arizona, Arkansas, California, Connecticut, Delaware, Hawaii, Idaho, Louisiana, Maine, Massachusetts, Michigan, Mississippi, Montana, Nebraska, Nevada, New Mexico, New York, North Carolina, North Dakota, Oregon, Rhode Island, South Carolina, South Dakota, Utah, Vermont, Washington, West Virginia, And Wyoming.
Overview
The Manager, Data Engineering is responsible for leading the design, implementation, operation, and modernization of the organization's enterprise data platform, lakehouse architecture, data integration ecosystem, and AI-ready data foundation. This role provides both technical leadership and people leadership across Data Engineering, Data Integration, DataOps, and enterprise data modernization initiatives. Operating within an Azure-first, Databricks-centric environment, the Manager, Data Engineering leads the organization's transition from traditional SQL-centric ETL architectures toward modern cloud-native lakehouse platforms utilizing Azure Databricks, Delta Lake, Unity Catalog, Azure Data Lake Storage Gen2, Azure Data Factory, APIs, event-driven architectures, and modern DataOps practices. This is a hands-on leadership role responsible for establishing enterprise data architecture standards, canonical data models, master data management strategies, data governance controls, data quality frameworks, integration patterns, and AI-ready data products supporting analytics, machine learning, intelligent automation, robotic process automation (RPA), generative AI, and operational decision-making.
The Manager, Data Engineering directly leads Data Engineers and Data Integration Engineers while remaining actively engaged in architecture, design reviews, platform modernization, solution delivery, and technical mentoring. The role partners closely with Software Engineering, Cloud Engineering, DevOps, Security, Analytics, Compliance, and business stakeholders to deliver scalable, secure, governed, and reusable enterprise data assets. The Manager, Data Engineering is accountable for both current-state ETL and integration operations as well as the long-term transformation toward cloud-native data platforms, lake house architectures, enterprise data products, and AI-enabled business capabilities.
Responsibilities
How do I make an impact on my team?
  • Lead and support the organizational data integration efforts by effectively developing and leading a team of data integration developers, engineers, architects, and managers.
  • Establish enterprise data architecture standards, canonical data models, data domains, and data product strategies.
  • Lead the modernization of legacy SQL Server ETL workloads into Azure Databricks and Lakehouse architectures.
  • Define and govern Bronze, Silver, and Gold data layer standards.
  • Establish enterprise data dictionaries, business glossaries, metadata management, and lineage standards.
  • Lead development of AI-ready data products supporting machine learning, predictive analytics, intelligent automation, RAG, and agentic AI solutions.
  • Define enterprise DataOps practices including CI/CD, automated testing, observability, data quality, and deployment automation.
  • Lead the design and implementation of data integration and data lake house solutions.
  • Lead collaboration efforts with IT teams to ensure robust and scalable data architecture is established and meeting company objectives.
  • Lead the establishment of data validation and reconciliation processes to maintain data accuracy.
  • Partner with business stakeholders to understand data requirements and deliver solutions that meet their needs.
  • Assess the current data services processes, identify challenges, quantify the business value, establish procedures to address challenges, and support the future state model and vision definition.
  • Stay current with industry trends and advancements in data integration and management technologies.
  • Lead healthcare data integration initiatives involving claims, eligibility, pharmacy, clinical, financial, operational, and partner data sources.
  • Serve as technical authority for data modeling, canonicalization, master data management, and enterprise data governance practices.
  • Provide direct leadership, coaching, hiring, and performance management for Data Engineers and Data Integration Engineers.
  • Participate in architecture reviews and remain actively engaged in solution design, platform modernization, and technical delivery.
  • Develop training plans to foster growth and development across functional areas to meet expanding technology needs. Research and develop learning needs for ongoing system developments with contractors.
  • Continuously review and monitor technology resources and gap analysis, establish criteria and make recommendations for advancement.
  • Develop and implement a comprehensive data management strategy aligned with strategic objectives. Establish resources, tools and direction for each functional leader.
  • Establish data integration policies and procedures to ensure data accuracy, security, and compliance with regulatory requirements.
  • Participate in, adhere to, and support compliance, people and culture, and learning programs.
  • Perform other duties as assigned.

Qualifications
What our team expects from you?
  • Education: Bachelor's degree in the field of computer science, information systems, or data science, or equivalent work experience, required.
  • Experience:
    • 10+ years of experience in Data Engineering, Data Architecture, Analytics Engineering, Data Integration, or Data Platform Engineering required.
    • 5+ years leading Data Engineering teams required.
    • Experience designing and implementing Databricks Lakehouse architecture required.
    • Experience establishing canonical data models, enterprise data products, metadata management, and governance frameworks required.
    • Experience supporting AI, machine learning, analytics, and automation initiatives through modern data engineering practices required.
    • Experience modernizing legacy ETL and SQL-based architectures into cloud-native platforms required.
    • Experience with healthcare data domains strongly preferred.
    • Advanced experience and skills in data ingestion, data architecture, and data integration techniques required.
    • Proficiency in data integration tools and languages (e.g., SQL, Linux, Python, ETL tool) required.

What can you expect from Archimedes?
  • Top of the industry benefits for Health, Dental, and Vision insurance
  • 20 days paid time off
  • 4 weeks paid parental leave
  • 9 paid holidays
  • 401K company match of up to 5% - No vesting requirement
  • Adoption Assistance Program
  • Flexible Spending Account
  • Educational Assistance Plan and Professional Membership assistance
  • Referral Bonus Program - up to $750!

Location : Address
Remote
Location : Country
US

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