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Databricks Data Engineer Jobs in Charlotte, NC (NOW HIRING)

Guidehouse

Senior Data Engineer

Charlotte, NC · On-site

$80K - $133K/yr

Implement and support cloud-native data platforms leveraging AWS, Azure, Databricks, and other modern technologies. * Design and implement CI/CD pipelines and DevOps best practices for data ...

Guidehouse

Public Health Data Engineer

Charlotte, NC · On-site

$111K - $134K/yr

Guidehouse seeks a Data Engineer to support the development, maintenance, and enhancement of data ... Exposure to Databricks, Spark, or large-scale data processing technologies. * Familiarity with AWS ...

Axiom Path

Senior Azure Data Engineer 3625215

Charlotte, NC · On-site

$103K - $140K/yr

Contribute to modernization efforts involving Azure Synapse, Azure Data Factory, and Databricks. Do you bring proven success in Azure data engineering and cloud data platform delivery? * 10+ years of ...

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Databricks Data Engineer information

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$43.5K

$126.7K

$173.4K

How much do databricks data engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for databricks data engineer in Charlotte, NC is $126,696.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,800.00 and $134,300.00 per year, depending on experience, location, and employer.

What is a Databricks data engineer?

A Databricks Data Engineer is responsible for designing, building, and maintaining scalable data pipelines on the Databricks platform. They work with Apache Spark, Delta Lake, and cloud services to process large datasets efficiently. Their role involves data ingestion, transformation, optimization, and ensuring data quality for analytics and machine learning. Additionally, they collaborate with data scientists, analysts, and business teams to deliver reliable data solutions.

What does a Databricks data engineer do?

A typical day for a Databricks Data Engineer involves developing and maintaining scalable data pipelines, optimizing big data workflows using Spark, and collaborating with data scientists, analysts, and other engineers. You will regularly work within cloud environments to manage and process large datasets, conduct troubleshooting, and ensure data reliability and performance. Daily tasks may also include writing code, participating in team meetings, and implementing best practices for data security and governance. This role is highly collaborative, requiring frequent communication to align on project goals and address any technical challenges. The dynamic, project-based structure helps expand your skills and offers growth opportunities into senior engineering or data architecture roles.

What are the key skills and qualifications needed to thrive as a Databricks data engineer?

To thrive as a Databricks Data Engineer, you need strong expertise in data engineering concepts, big data processing, and programming languages such as Python, Scala, or SQL, often supported by a degree in computer science or a related field. Proficiency in Databricks, Apache Spark, cloud platforms (like AWS, Azure, or GCP), and relevant certifications such as Databricks Certified Data Engineer are highly valued. Effective problem-solving, collaboration, and clear communication skills help engineers work efficiently within cross-functional teams. These skills are essential for designing scalable data pipelines, ensuring data quality, and delivering actionable analytics in dynamic business environments.

How much does a Databricks data engineer make?

A Databricks Data Engineer typically earns between $90,000 and $150,000 annually, depending on experience, location, and certifications. Senior roles or those with advanced skills in Spark, cloud platforms, and data pipeline development can earn higher salaries.

Is a 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 the most commonly searched types of Databricks Data Engineer jobs in Charlotte, NC?

The most popular types of Databricks Data Engineer jobs in Charlotte, NC are:

What are popular job titles related to Databricks Data Engineer jobs in Charlotte, NC?

For Databricks Data Engineer jobs in Charlotte, NC, the most frequently searched job titles are:

What job categories do people searching Databricks Data Engineer jobs in Charlotte, NC look for?

The top searched job categories for Databricks Data Engineer jobs in Charlotte, NC are:

What cities near Charlotte, NC are hiring for Databricks Data Engineer jobs?

Cities near Charlotte, NC with the most Databricks Data Engineer job openings:

Databricks Data Engineer jobs near you
Infographic showing various Databricks Data Engineer job openings in Charlotte, NC as of August 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 89% In-person, 2% Hybrid, and 9% Remote job distribution, with an average salary of $126,696 per year, or $60.9 per hour.

CCAR Data Engineer, Associate

Sumitomo Mitsui Financial Group, Inc.

Charlotte, NC • On-site

Full-time

Posted 27 days ago

Key responsibilities

  • Design, develop, and support scalable data pipelines and platforms using Databricks, PySpark, Python, SQL, and Delta Lake.

  • Build and maintain data sourcing, ingestion, and execution frameworks for CCAR, Stress Testing, and Regulatory Reporting.

  • Implement data quality controls, reconciliation processes, and develop workflows for data adjustments, attestations, and regulatory reporting governance.

Job description

SMBC Group is a top-tier global financial group. Headquartered in Tokyo and with a 400-year history, SMBC Group offers a diverse range of financial services, including banking, leasing, securities, credit cards, and consumer finance. The Group has more than 130 offices and 80,000 employees worldwide in nearly 40 countries. Sumitomo Mitsui Financial Group, Inc. (SMFG) is the holding company of SMBC Group, which is one of the three largest banking groups in Japan. SMFG's shares trade on the Tokyo, Nagoya, and New York (NYSE: SMFG) stock exchanges.
In the Americas, SMBC Group has a presence in the US, Canada, Mexico, Brazil, Chile, Colombia, and Peru. Backed by the capital strength of SMBC Group and the value of its relationships in Asia, the Group offers a range of commercial and investment banking services to its corporate, institutional, and municipal clients. It connects a diverse client base to local markets and the organization's extensive global network. The Group's operating companies in the Americas include Sumitomo Mitsui Banking Corp. (SMBC), SMBC Nikko Securities America, Inc., SMBC Capital Markets, Inc., SMBC MANUBANK, JRI America, Inc., SMBC Leasing and Finance, Inc., Banco Sumitomo Mitsui Brasileiro S.A., and Sumitomo Mitsui Finance and Leasing Co., Ltd.
Role Description
SMBC is driving a major Digital Transformation initiative across its Americas Division, with a strong focus on modernizing technology platforms, enhancing data-driven decision-making, and supporting business growth. As part of this transformation, we are seeking a talented Data Engineer to join the Regulatory Reporting & CCAR Technology Team.
The Data Engineer will be responsible for developing scalable data platforms on Databricks that support end-to-end data sourcing, CCAR model execution, data adjustments, result overlays, and attestation workflows. This role requires strong expertise in Databricks, PySpark, Python, and AI/ML technologies to build robust, auditable, and regulatory-compliant solutions. The individual will collaborate closely with Finance, Risk, Data Management, and Model Development teams to deliver innovative data engineering solutions that enhance regulatory reporting processes and operational efficiency.
Key Responsibilities
  • Design, develop, and support scalable data pipelines using Databricks, PySpark, Python, SQL, and Delta Lake.
  • Build and maintain data sourcing and ingestion frameworks for CCAR, Stress Testing, and Regulatory Reporting.
  • Develop and support platforms for CCAR model execution, including PPNR, Balance Sheet, RWA, and other risk models.
  • Implement data quality controls, reconciliation processes, lineage tracking, and audit capabilities.
  • Develop solutions for data adjustments, management overlays, business overrides, and exception management workflows.
  • Build and enhance attestation, approval, and sign-off workflows for regulatory reporting governance.
  • Partner with Finance, Risk, and Regulatory Reporting stakeholders to deliver business-critical solutions.
  • Leverage AI/ML capabilities for data quality monitoring, anomaly detection, intelligent automation, and operational insights.
  • Support CI/CD, production releases, troubleshooting, performance tuning, and operational support activities.

Qualifications and Skills
  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
  • 7+ years of experience in Data Engineering, Data Platform Development, or Analytics Engineering.
    • Strong hands-on experience with: Azure Data Factory, Databricks, PySpark, Python, SQL, Delta Lake, GitHub and CI/CD
  • Experience building cloud-native and distributed data processing solutions.
  • Strong understanding of ETL/ELT architectures, data modeling, data governance, and data quality frameworks.
  • Knowledge of AI/ML concepts, machine learning lifecycle management, and model operationalization.
  • Excellent analytical, problem-solving, communication, and stakeholder management skills.

Preferred Qualifications
  • Experience supporting CCAR, FR Y-14 Regulatory Reporting, Stress Testing, Capital Planning, Risk Management, or Finance Technology initiatives.
  • Experience developing solutions for:
    • Data sourcing and reconciliation
    • Model execution platforms
    • Data adjustments and result overlays
    • Attestation and workflow management
  • Experience with MLflow, Databricks Workflows, Azure Data Factory, Azure SQL, Azure Functions, REST APIs, and Azure Cloud Services.
  • Experience migrating analytical models from R to Python and deploying AI/ML solutions into production.
  • Knowledge of model governance, model risk management, audit controls, and regulatory compliance requirements.
  • Experience working in highly regulated financial services environments with strong governance and audit requirements.

SMBC's employees participate in a Hybrid workforce model that provides employees with an opportunity to work from home, as well as, from an SMBC office. SMBC requires that employees live within a reasonable commuting distance of their office location. Prospective candidates will learn more about their specific hybrid work schedule during their interview process. Hybrid work may not be permitted for certain roles, including, for example, certain FINRA-registered roles for which in-office attendance for the entire workweek is required.
SMBC provides reasonable accommodations during candidacy for applicants with disabilities consistent with applicable federal, state, and local law. If you need a reasonable accommodation during the application process, please let us know at accommodations@smbcgroup.com.

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