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Trainee Databricks Data Engineer Jobs in Springfield, MA

Data Strategy-Manager

Hartford, CT · On-site

$99K - $232K/yr

... Databricks Certified Data Engineer / Data Analyst / ML - Proven leadership in data-driven strategies - Experience in defining data governance frameworks - Understanding of modern cloud data ...

Azure Databricks Admin

Hartford, CT · On-site

$55.50 - $68.75/hr

... Technology|Data Engineering|Databricks Technical Skills 2 Technology|AI Engineering|Databricks AI Engineering Services Overview The Infosys Data and Analytics (DNA) unit is at the forefront of ...

Data Governance- Manager

Hartford, CT · On-site

$99K - $232K/yr

... Databricks Certified Data Engineer / Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $99,000 - $232,000. Actual compensation within the ...

... engineering teams and modernizing technology & data platforms. Our delivery models are tailored to ... Experience with Databricks MLOps or infrastructure setup * Experience coordinating delivery teams ...

Senior Data Architect

Windsor, CT

$66.75 - $89.50/hr

This role works directly with business, architecture, and engineering teams to define scalable data ... Hands‑on experience with Spark, Databricks, and Python/SQL * Snowflake expertise Preferred Skills:

Senior Data Architect

Windsor, CT

$66.75 - $89.50/hr

You'll work directly with business, architecture, and engineering teams to define scalable data ... Hands-on with Spark, Databricks, Python/SQL * Snowflake expertise Preferred Skills: * BigQuery ...

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Showing results 1-20

Trainee Databricks Data Engineer information

See Springfield, MA salary details

$44.3K

$129.3K

$176.9K

How much do trainee databricks data engineer jobs pay per year?

As of Jun 21, 2026, the average yearly pay for trainee databricks data engineer in Springfield, MA is $129,263.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,100.00 and $137,000.00 per year, depending on experience, location, and employer.

Is it hard to get hired at Databricks?

Getting hired as a Databricks Data Engineer can be competitive, as it requires strong skills in Spark, cloud platforms, and data pipeline development. Candidates often need relevant experience, technical certifications, and a solid understanding of big data tools to improve their chances.

Does Databricks hire new grads?

Databricks often hires new graduates for entry-level roles such as Trainee Data Engineer positions. These roles typically require familiarity with cloud platforms, data processing tools, and programming languages like Python or SQL. Candidates should review specific job postings for qualification details and preferred skills.

How much do Databricks data engineers make?

Databricks data engineers typically earn between $90,000 and $140,000 annually, depending on experience, location, and skill level. Professionals with expertise in Spark, cloud platforms, and data pipeline development tend to command higher salaries.

What is the difference between Trainee Databricks Data Engineer vs Junior Data Engineer?

AspectTrainee Databricks Data EngineerJunior Data Engineer
Required CredentialsBasic knowledge of Databricks, SQL, and data fundamentalsDegree in Computer Science or related field, some experience with data tools
Work EnvironmentTraining programs, mentorship, entry-level projects on Databricks platformEntry-level to mid-level data teams, real-world data projects
Employer & Industry UsageTech companies, data consulting firms, startups focusing on cloud data platformsVariety of industries including finance, healthcare, retail, with data teams

The Trainee Databricks Data Engineer is an entry-level role focused on learning Databricks and data engineering fundamentals, often within training programs. In contrast, a Junior Data Engineer typically has some hands-on experience and works on real data projects. Both roles are common in tech-driven industries, but the trainee position emphasizes skill development, while the junior role involves more independent work.

Is Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and big data processing. Skills in Apache Spark, cloud environments, and data pipeline development are highly sought after, leading to strong job growth in this field.
What are popular job titles related to Trainee Databricks Data Engineer jobs in Springfield, MA? For Trainee Databricks Data Engineer jobs in Springfield, MA, the most frequently searched job titles are:
What job categories do people searching Trainee Databricks Data Engineer jobs in Springfield, MA look for? The top searched job categories for Trainee Databricks Data Engineer jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Trainee Databricks Data Engineer jobs? Cities near Springfield, MA with the most Trainee Databricks Data Engineer job openings:
Senior Forward Deployed Engineer - Databricks

Senior Forward Deployed Engineer - Databricks

Deloitte

Hartford, CT

$105K - $144K/yr

Other

Posted yesterday


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

At Deloitte, Senior Forward Deployed Engineers (SFDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on September 30, 2026

Work you'll do

As a Senior Databricks FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include: 

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.
  • Coach client teams and end users on platform capabilities and AI enablement, while building trusted relationships, managing expectations, and supporting long-term engagement success.
  • Drive end-to-end sales and delivery support by developing demos/POCs, contributing to proposals and orals, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer.
  • Strengthen team and organizational impact by mentoring other FDEs through design/code reviews and feedback, while contributing reusable components to intellectual capital.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Databricks including hands on experience with one of the following key platform technologies; DBRX, MLflow, Vector Search, Databricks AI Gateway
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code o
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

At Deloitte, Senior Forward Deployed Engineers (SFDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on September 30, 2026

Work you'll do

As a Senior Databricks FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include: 

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.
  • Coach client teams and end users on platform capabilities and AI enablement, while building trusted relationships, managing expectations, and supporting long-term engagement success.
  • Drive end-to-end sales and delivery support by developing demos/POCs, contributing to proposals and orals, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer.
  • Strengthen team and organizational impact by mentoring other FDEs through design/code reviews and feedback, while contributing reusable components to intellectual capital.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Databricks including hands on experience with one of the following key platform technologies; DBRX, MLflow, Vector Search, Databricks AI Gateway
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code o
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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