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Remote Databricks Architect Jobs in Worcester, MA

thg

Senior Data Engineer (HYBRID in MA or REMOTE)

Worcester, MA · On-site +1

$105K - $143K/yr

The engineer will understand where the data is, basic data models and architecture, how to access ... Proven experience using Databricks and delta live tables in a data engineering context * Experience ...

thg

Senior Data Engineer (HYBRID in MA or REMOTE)

Worcester, MA · On-site +1

$105K - $143K/yr

The engineer will understand where the data is, basic data models and architecture, how to access ... Proven experience using Databricks and delta live tables in a data engineering context * Experience ...

All JobsRemote Databricks Architect JobsRemote Databricks Architect Jobs in Worcester, MA

Remote Databricks Architect information

See Worcester, MA salary details

$10

$69

$95

How much do remote databricks architect jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for remote databricks architect in Worcester, MA is $69.91, according to ZipRecruiter salary data. Most workers in this role earn between $62.12 and $81.54 per hour, depending on experience, location, and employer.

Can you work remotely as an architect?

Remote work is possible for a Databricks Architect, especially with the increasing adoption of flexible work arrangements in the tech industry. Many organizations allow architects to perform their duties remotely, utilizing cloud platforms, collaboration tools, and virtual communication. However, some roles may require on-site presence for meetings, training, or specific project needs.

Does Databricks allow remote work?

Remote Databricks Architects can often work remotely, depending on the company's policies and project requirements. Many organizations in data engineering and analytics support remote work, especially for roles involving cloud platforms and tools like Databricks, which facilitate collaboration and remote access. Candidates should verify specific employer policies and ensure they have the necessary technical setup for remote work environments.

What is the difference between Remote Databricks Architect vs Remote Data Engineer?

AspectRemote Databricks ArchitectRemote Data Engineer
Primary FocusDesigning and implementing data solutions on Databricks platformBuilding and maintaining data pipelines and infrastructure
Required SkillsDatabricks, Spark, cloud platforms, architecture designETL, SQL, Python, cloud data tools
CertificationsDatabricks certifications, cloud certificationsCloud certifications, SQL, Python skills
Work EnvironmentCollaborates with data teams, architects, and stakeholdersWorks on data pipeline development, data modeling

While both roles work within data environments and often in cloud settings, the Remote Databricks Architect focuses on designing scalable data solutions using Databricks, whereas the Remote Data Engineer primarily builds and maintains data pipelines and infrastructure. The architect role emphasizes architecture and strategy, while the data engineer role emphasizes implementation and operational tasks.

Will AI replace Solution Architect?

AI is unlikely to fully replace Solution Architects, as their role involves complex problem-solving, designing scalable systems, and understanding business needs that require human judgment. Instead, AI tools can augment their work by automating routine tasks and providing data-driven insights, allowing Solution Architects to focus on strategic planning and innovative solutions. Success in this role often depends on technical expertise, communication skills, and experience with cloud platforms like Databricks.

How much do Databricks architects make?

Databricks architects typically earn between $120,000 and $180,000 annually, depending on experience, location, and certifications. Senior roles or those with specialized skills in cloud platforms and big data tools may command higher salaries.
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Remote Databricks Architect jobs near you

Senior Data Engineer (HYBRID in MA or REMOTE)

thg

Worcester, MA • On-site, Remote

$105K - $143K/yr

Other

Posted 7 days ago

Job description

Our Claims Analytics team is currently seeking a Senior Data Engineer to join our growing team in our Worcester, MA office, hybrid or remote work arrangement.    

This is a full-time, exempt position. 

POSITION OVERVIEW: 

Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis.  This role primarily will become proficient with all internal & external data produced and consumed by THG.

The engineer will understand where the data is, basic data models and architecture, how to access and obtain data and how to manipulate and work with data to produce output – which may be reports, datasets or self-service reports.

The ideal candidate is a selfmotivated, adaptable, and composed collaborator who learns quickly, thinks with a bigpicture mindset, and leads by example to help set the tone and standards for the team.

IN THIS ROLE, YOU WILL: 

  • Drive larger, more complicated projects independently and ability to handle multiple projects simultaneously.
  • Develop scalable and efficient data models, data structures, and ETL pipelines that support analytics, reporting, and downstream consumption.
  • Consistently prioritize data quality by implementing validation checks, monitoring accuracy and completeness, and clearly documenting data pipelines and processes.
  • Collaborate with business partners and cross-functional teams on data/reporting requests.
  • Be accountable for successful outcomes related to designing, developing, implementing, optimizing, and maintaining data pipelines and solutions.
  • Lead with an ownership mindset to design, implement, and continuously improve data governance, controls, and standards, ensuring the platform is secure, compliant, and scalable.
  • Prioritize work effectively by balancing business impact, technical risk, and domain knowledge to deliver the highestvalue outcomes.
  • Coach and mentor less senior team members, as well as conducting reviews for their work 

WHAT YOU NEED TO APPLY:  

  • Bachelor’s degree or higher in Data Science, Mathematics, Statistics, Computer Science, Information Systems, Business Information Technology, or equivalent 
  • 8+ years professional experience in data engineering, data architecture, or data analytics
  • Proficiency in the following languages: Advanced SQL, Python, Java, Scala (nice to have).
  • Proficient in building SQL stored procedures, ETL pipelines using Azure Synapse (Synapse Pipelines / Data Factory).
  • Holds active Azure DP-203 (Microsoft Certified: Azure Data Engineer Associate) or equivalent. Other Azure DP certifications or equivalents are also applicable
  • Familiarity in insurance data (Claims data is highly preferred).
  • Data Modeling: Creation of conceptual, logical, and physical data models for data objects, object attributes, and their relationships
  • Analytical Skills: Data Engineers work with large amounts of data that will include facts, figures, and number crunching.  You will need to profile the data and analyze it to find conclusions.
  • Communication Skills: Data engineers are often called to present their findings or translate the data into an understandable document.  You will need to write and speak clearly, easily communicating complex ideas.
  • Critical Thinking: Data engineers must look at the numbers, trends, and data and come to new conclusions based on the findings.
  • Attention to Detail: Data is precise.  Data engineers must make sure they are vigilant in their analysis to come to correct conclusions.
  • Math Skills: Data engineers need advanced math skills to estimate numerical data.  Insurance experience required as well as insurance products.
  • Debugging Skills: Data engineers need the ability to analyze issues with components in our data solutions and come up with remediation plans.
  • Proven experience in data engineering, implementation of best practices for data storage, access, integration, transformation, etc., within Azure
  • Proven experience using Databricks and delta live tables in a data engineering context
  • Experience in optimizing data pipelines to account for scale, performance, reliability, and cost efficiency
  • Demonstrated proficiency in relational, NoSQL, hierarchical, and entity relationship data modeling
  • Experience in creating easy to consume documentation of data processes and solutions to aid in knowledge transfer and continuity.
  • Experienced in agile development methodologies, developing high quality code, and DevOps best practices
  • Must be eligible to work in the United States without requiring sponsorship now or in the future (ie. lawful permanent residence or US citizen)

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