Remote Data Engineer - & Modeler Informatica
NTT DATAAbout the role
Req ID: 378301
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, apply now.
We are currently seeking a Remote Data Engineer - & Modeler Informatica to join our team in Plano, Texas (US-TX), United States (US).
Role Overview
We are seeking an Intermediate-Level Data Engineer & Data Modeler to focus on designing, building, and maintaining data pipelines and data models that enable scalable, high-quality data products across the organization.
Key Responsibilities
Data Engineering & Pipeline Development
• Design, build, and maintain ETL/ELT data pipelines for data ingestion and transformation
• Develop data integration workflows to support enterprise analytics
• Implement scalable data processing frameworks and automation pipelines
• Monitor pipeline execution and ensure data availability and reliability
Data Modeling & Design
• Design logical and physical data models to support business requirements
• Define data structures, relationships, and schemas across domains
• Develop standardized data layers (e.g., Bronze/Silver/Gold)
• Collaborate with stakeholders on data mappings and business logic
Data Integration & Quality
• Perform source-to-target mapping and transformation design
• Implement data quality checks and validation rules
• Maintain data lineage, metadata, and documentation
• Support integration of enterprise data sources
Production Support & Optimization
• Provide L2/L3 support for data pipelines
• Monitor and optimize pipeline performance
• Perform root cause analysis and issue resolution
• Support job scheduling and error handling processes
Collaboration & Delivery
• Work with data architects, analysts, and BI teams
• Translate business requirements into technical solutions
• Support data platform modernization initiatives
• Participate in Agile processes such as sprint planning and code reviews
Basic Qualifications
• 6+ years of experience in Data Engineering and/or Data Modeling
• 6+ years of experience building and maintaining enterprise data pipelines
• 6+ years of experience working with large, complex datasets
Technical Skills
• Strong SQL and data modeling expertise
• Experience with ETL/ELT tools (Informatica, DataStage, ADF, etc.)
• Experience with Python, Spark, or similar frameworks
• Familiarity with platforms such as Snowflake, Databricks, or Azure Data Lake
• Knowledge of pipeline orchestration and integration patterns
Preferred Qualifications
• Experience with Azure-based data platforms
• Exposure to data governance and metadata management tools
• Experience in healthcare or regulated environments
• Experience supporting data modernization initiatives
Key Success Metrics
• Reliable and timely pipeline execution
• High-quality data models supporting analytics
• Improved data quality and reduced errors
NTT DATA provides a reasonable range of compensation for U.S.-based positions. The starting pay range for this role is $121,162 - $224,375 per year. Actual compensation will depend on a number of factors, including the candidate’s relevant experience, technical skills, and other qualifications. This position may also be eligible for incentive compensation based on individual and/or company performance.
This position is eligible for company benefits including medical, dental, and vision insurance with an employer contribution, flexible spending or health savings account, life and AD&D insurance, short and long term disability coverage, paid time off, employee assistance, participation in a 401k program with company match, and additional voluntary or legally-required benefits.
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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,
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