Senior Data Engineer

NTT DATA; Charlotte (NC); Hybrid; USD 140,000 - 190,000; Full time

Job summary

NTT DATA is seeking a Senior Data Engineer to design and optimize data pipelines using Databricks, Python, PySpark, and SQL. You will build document ingestion and extraction work streams, integrate LLMs into processing workflows, and implement robust data quality controls.

The role involves designing ontology-based data models, mapping attributes to ontology concepts, and ensuring scalable, reliable delivery for underwriting workflows. Collaboration with cross-functional teams is key.

Qualifications

• 7+ years of experience in data engineering, software development, or production data pipeline development.
• 4+ years of hands-on experience with Databricks and scalable data-processing pipelines.
• 5+ years of experience with Python, PySpark, and SQL.
• 3+ years of experience processing unstructured and semi-structured data (PDFs, emails, Excel, JSON).
• 2+ years of experience integrating LLMs or AI models into data-processing pipelines.
• 3+ years of experience implementing structured data extraction, document classification, validation, reconciliation, and data-quality controls.

Responsibilities

• Design, develop, and optimize scalable data pipelines using Databricks, Python, PySpark, and SQL.
• Build document ingestion, classification, extraction, validation, and transformation pipelines for various documents.
• Integrate LLMs and AI models into data-processing workflows to extract structured information.
• Implement document classification, source-specific extraction rules, data validation, reconciliation, and QC mechanisms.
• Transform extracted information into standardized JSON structures for downstream applications.
• Design ontology-based data models and map attributes to ontology concepts and metadata.

Skills

Databricks

Python

PySpark

SQL

LLMs integration

Data modeling

PostgreSQL

Cloud architectures

API development

Data pipelines

Education

Bachelor's degree in Computer Science / Information Technology / Data Engineering

Tools

Databricks Workflows

Delta Lake

Lakehouse

APIs

SQL tooling

Job description

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization,

Job Description – Senior Data Engineer (Databricks / AI Document Processing / Ontology)

Day-to-Day Job Duties: (What this person will do on a daily/weekly basis)

• Design, develop, and optimize scalable data pipelines using Databricks, Python, PySpark, and SQL.
• Build document ingestion, classification, extraction, validation, and transformation pipelines for PDFs, emails, attachments, Excel/XLSX files, insurance applications, Statements of Values (SOVs), and other business documents.
• Integrate LLMs and AI models into data-processing workflows to extract structured information from unstructured and semi-structured documents.
• Troubleshoot false positives, incorrect metadata, and inaccurate field values generated by LLM-based extraction pipelines.
• Implement document classification, source-specific extraction rules, data validation, reconciliation, and quality-control mechanisms.
• Transform extracted information into standardized JSON structures for downstream applications and underwriting workflows.
• Design and implement ontology-based data models representing insurance entities, business concepts, and relationships.
• Map extracted document attributes to standardized ontology concepts and metadata structures.
• Optimize the processing of large and complex Excel/XLSX and SOV files, addressing performance, scalability, and concurrency challenges.
• Implement reliable data persistence using PostgreSQL, Lakebase, or related database technologies.
• Develop and maintain APIs and data products to support downstream application integration.
• Collaborate with brokerage, underwriting, AI, and data engineering teams to align extraction outputs with business requirements.
• Monitor production pipelines, troubleshoot data-processing issues, and continuously improve reliability, performance, and data quality.

Basic Qualifications: (What are the skills required for this job with minimum years of experience on each)

• Minimum 7+ years of experience in data engineering, software development, or production data pipeline development.
• Minimum 4+ years of hands‑on experience with Databricks and scalable data-processing pipelines.
• Minimum 5+ years of experience with Python, PySpark, and SQL.
• Minimum 3+ years of experience processing unstructured and semi-structured data, including PDFs, emails, Excel files, JSON, and business documents.
• Minimum 2+ years of experience integrating LLMs or AI models into document-processing or data-extraction pipelines.
• Minimum 3+ years of experience implementing structured data extraction, document classification, validation, reconciliation, and data-quality controls.
• Strong understanding of data modeling, schemas, metadata, entity relationships, and ontology or semantic modeling concepts.
• Minimum 2+ years of experience designing JSON outputs, APIs, and data products for downstream application consumption.
• Minimum 2+ years of experience with PostgreSQL, Lakebase, or similar relational database technologies.
• Minimum 2+ years of experience troubleshooting production performance, scalability, concurrency, and data-processing issues.
• Strong understanding of cloud-based data architectures, distributed processing, and pipeline optimization.
• Strong analytical, problem-solving, communication, and cross-functional collaboration skills.

Travel: NA

Degree:

Bachelor’s degree in Computer Science, Information Technology, Data Engineering, Engineering, or a related field, or equivalent professional experience.

Nice to Have:

• Experience in insurance, commercial insurance, brokerage, underwriting, or risk management.
• Experience processing insurance applications, Statements of Values (SOVs), policy documents, and underwriting submissions.
• Experience with LLM frameworks, prompt engineering, structured outputs, and AI evaluation techniques.
• Experience building custom ontologies, knowledge graphs, or semantic data layers.
• Experience with document AI, OCR, information extraction, and document intelligence platforms.
• Experience with Delta Lake, Lakehouse architecture, Databricks Workflows, and Delta Live Tables.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience optimizing large-scale document ingestion and distributed processing workloads.

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees.

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