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Remote Databricks Data Engineer Jobs in Maryland

Perform exploratory data analysis, data cleaning, and feature engineering to support modeling and ... Databricks, container-based deployments, or similar MLOps tooling) * Insurance or financial ...

Work with data science and data engineering teams to build data pipelines, improve internal systems ... Ability to work effectively and independently in a remote role, managing multiple priorities and ...

Work with data science and data engineering teams to build data pipelines, improve internal systems ... Ability to work effectively and independently in a remote role, managing multiple priorities and ...

We're data geeks to our core, committed to simplifying the toughest challenges and operating with ... This specific role is primarily remote, with occasional travel to an office or client site.

... data platforms (Databricks, Snowflake), and cloud-native applications, identifying and mitigating ... remote-first culture - you've come to the right place. What Does This Mean for You? At Aledade, you ...

... and/or remote client service delivery. Recruiting for this role ends on 06/30/2026. Work you'll do As a GCP Engineer on the AI & Data team, you will be responsible for... * Build, configure, and ...

... data platforms (Databricks, Snowflake), and cloud-native applications, identifying and mitigating ... remote-first culture - you've come to the right place. What Does This Mean for You? At Aledade, you ...

United States (Remote) Interested applicants must reside in one of the following approved states ... Collaborate with data engineering teams to translate architecture designs into scalable physical ...

Senior Data Architect (Remote)

Baltimore, MD · Remote

$66.75 - $89.50/hr

Provide technical leadership and mentorship to data engineers, data modelers, and analysts. Stay updated on industry trends and emerging technologies for cloud computing, analytics, and AI. * Data ...

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Remote Databricks Data Engineer information

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

To thrive as a Remote Databricks Data Engineer, you need a solid background in data engineering, strong programming skills in Python or Scala, and experience with big data frameworks, often supported by a degree in computer science or a related field. Proficiency with Databricks, Apache Spark, cloud platforms (such as AWS or Azure), and relevant certifications like Databricks Certified Data Engineer are highly valuable. Strong problem-solving abilities, effective remote communication, and collaboration skills set top performers apart in distributed teams. These skills and qualities ensure efficient data pipeline development, seamless integration, and successful project delivery in remote environments.

What are some common challenges faced by remote Databricks Data Engineers and how can they be addressed?

Remote Databricks Data Engineers often encounter challenges such as coordinating efficiently with distributed teams, managing access to secure data environments, and ensuring smooth pipeline deployments across different cloud platforms. To overcome these, it's important to leverage communication tools for regular check-ins, follow strict data governance protocols, and utilize collaborative features in Databricks such as shared notebooks and version control. Proactively documenting your work and staying updated with platform updates can also help streamline remote collaboration and problem-solving.

What is a Remote Databricks Data Engineer?

A Remote Databricks Data Engineer is a professional who designs, develops, and manages large-scale data processing systems using the Databricks platform, often working from a remote location. They focus on building data pipelines, integrating data sources, and optimizing workflows for analytics and machine learning, leveraging tools like Apache Spark within Databricks. These engineers collaborate with data scientists, analysts, and other stakeholders to ensure data is accessible, reliable, and scalable for business needs. Remote roles offer flexibility in work location while still requiring strong communication and technical skills.
What are the most commonly searched types of Databricks Data Engineer jobs in Maryland? The most popular types of Databricks Data Engineer jobs in Maryland are:
What cities in Maryland are hiring for Remote Databricks Data Engineer jobs? Cities in Maryland with the most Remote Databricks Data Engineer job openings:
Data Scientist

Data Scientist

United Educators

Bethesda, MD • On-site, Remote

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago


Job description

The Data Scientist supports the Actuarial & Data Science Department's mission of advancing the use of data and analytical modeling in critical company decision-making. This role is responsible for performing rigorous statistical analyses, developing and validating predictive models, and building data-driven solutions that improve business processes, insights, and decision support across actuarial, underwriting, and operational functions. 

The Data Scientist works closely with cross-functional stakeholders to translate business problems into well-reasoned analytical solutions, from exploratory analysis and feature engineering through model development, validation, and deployment. The role also contributes to emerging AI initiatives, including the practical application of generative AI tools to augment productivity and analytical workflows, where appropriate. 

This role requires someone who understands both the how and why of machine learning and statistical modeling, not just the application of tools, but the underlying theory, tradeoffs, and limitations. Strong coding skills and the intellectual curiosity to stay current with a rapidly evolving technical landscape are essential. 

Responsibilities:

  • Perform exploratory data analysis, data cleaning, and feature engineering to support modeling and analytical initiatives
  • Develop, validate, and maintain predictive models and analytical frameworks, with a strong emphasis on model interpretability, rigor, and appropriate use
  • Build and maintain dashboards, reports, and visualizations to communicate insights clearly and effectively
  • Collaborate with actuarial, underwriting, finance, IT, and business stakeholders to translate business needs into analytical solutions
  • Ensure data quality, model integrity, and responsible modeling practices - including documentation, validation, and transparency on methodologies, assumptions, and model logic
  • Identify opportunities to apply generative AI and agentic tools to enhance productivity, automate workflows, or support analytical work, and contribute to prototyping and evaluating those use cases
  • Support integration of analytical and AI solutions into business workflows, including testing, validation, and user adoption
  • Contribute to best practices in data science, modeling, and responsible AI use across the organization
  • Stay current with developments in machine learning, data science, and applied AI, and bring forward relevant opportunities with sound judgment about fit and feasibility
  • Ability to independently execute projects from problem definition through deployment 

Requirements: 

  • Typically requires 5 years of relevant experience with requisite competencies
  • Bachelor's degree in relevant field (mathematics, statistics, data science, or computer science)
  • Proficiency in Python and SQL required, R experience a plus
  • Strong foundation in statistical theory, machine learning methods, and model evaluation - including a genuine understanding of when and why to apply different approaches
  • Experience with feature engineering, model validation, and working with large, complex datasets
  • Ability to write, read, and review code critically - not just run notebooks or adapt existing scripts
  • Experience with data visualization tools (e.g., Power BI)
  • Familiarity with AI/GenAI tools and APIs (e.g., LLMs, prompt engineering, agentic workflows) and genuine interest in applying them practically - preferred but not required
  • Strong problem-solving skills and attention to detail
  • Effective communication skills, including the ability to explain technical concepts and model behavior to non-technical stakeholders
  • Familiarity with cloud-based ML infrastructure, preferably Azure (e.g., Azure Machine Learning, Azure Databricks, container-based deployments, or similar MLOps tooling)
  • Insurance or financial services experience preferred 

Benefits:

  • Health Insurance - We offer subsidized plan options with an optional pre-tax Health Savings Account (HSA), including an annual employer contribution and investment options. The plans offer a prescription benefit and telehealth
  • Dental Insurance - Two plan levels are available, depending on needs
  • Vision Insurance -We offer in- and out-of-network options; Lasik discounts are available.
  • 401(k) - UE makes a 3% safe harbor non-elective contribution beginning the first of the month after date of hire; these funds are vested immediately. After one year of service, employees receive a 7% profit sharing non-elective contribution, as well as become eligible for a matched contribution of 25% of the first 5% employee deferral. Employees can make pre-tax contributions or taxed (Roth) salary reductions. Catch-up contributions for employees 50 years old and over. Employer contributions are fully vested immediately
  • Life Insurance - UE pays for Basic Life Insurance, and employees have the option to apply for additional Voluntary coverage
  • Short- and Long-Term Disability Insurance - We offer coverage in the event employees are unable to work for a period of time
  • For the first two years of employment, employees accrue PTO at 24 days per year. At the beginning of the third year of service, employees accrue 30 days per year of PTO
  • 11 paid holidays annually including Juneteenth and an employee choice floating holiday
  • Bonus eligibility is based on salary earned and performance for the year
  • Hybrid environment - employees are typically in the office 2-3 days per week after the initial training period
  • Inclusive and supportive culture that embraces diversity and provides opportunities for all to succeed
  • Monthly lunches and various social events throughout the year
  • Opportunities to join the Social Committee, Employee Resource Groups (ERGs), and Inclusion, Diversity, and Equity Alliance (IDEA)