Own solution architecture for the platform and new data-visualisation components for a major data transformation and services programme in the public sector infrastructure.
Responsibilities
Own solution architecture for the platform and new data-visualisation components
Build in scalability, security and performance and align to client architectural governance
Define standards, run architecture reviews and document design decisions
Lead a 6-person technical team across Architecture, DevOps, Data and Development
Provide technical leadership/mentoring and act as escalation point for blockers
Database Administrator supporting the Department of Health and Human Services (HHS).
Responsibilities
Creating new database solutions and implementing them properly based on overall project requirements
Monitoring overall database performance to ensure end users are receiving the information needed in as little time as possible
Troubleshooting performance issues, identifying the problem and promptly fixing it
Running tests on the new solution to ensure it functions correctly before fully rolling it out
Controlling access and permissions for accessing customer databases including verifying access requests and revoking access as directed by the customer
Support the renewal of a marketing automation solution by building data engineering and integration pipelines between Databricks and marketing platforms.
Responsibilities
Design, build, and maintain reliable data and integration pipelines between Databricks and marketing automation platforms
Develop transformations and data models for customer, behavioral, campaign, and event data
Integrate systems using APIs, JSON payloads, webhooks, and platform-specific connectors
Configure and develop data flows through Iterable Smart Sync and Iterable
Establish data-quality controls, validation rules, monitoring, and troubleshooting processes
Requirements
Nice to have: Iterable Smart Sync
Nice to have: other marketing automation platforms
Lead the design, build, and maintenance of data and integration pipelines between Databricks and marketing automation platforms, while contributing to MarTech solution development.
Responsibilities
Design, build, and maintain reliable data and integration pipelines between Databricks and marketing automation platforms
Develop transformations and data models for customer, behavioral, campaign, and event data
Integrate systems using APIs, JSON payloads, webhooks, and platform-specific connectors
Configure and develop data flows through Iterable Smart Sync and Iterable
Establish data-quality controls, validation rules, monitoring, and troubleshooting processes
Design, build and optimize scalable enterprise data solutions, including data ingestion, transformation, integration and lakehouse pipelines.
Compensation
NTT DATA provides a reasonable range of compensation for Canada-based positions. The starting pay range for this role is $88,528.00 to $110,660.00. This range reflects the minimum and maximum target compensation for the position across all Canada locations.
Responsibilities
Design and build scalable data pipelines
Optimize data ingestion and transformation processes
The Data Engineer will build, manage and optimize data pipelines and move these data pipelines effectively into production for key data and analytics consumers like business/data analysts, data scientists or any business partner that needs curated data for data and analytics use cases across the enterprise.
Responsibilities
Create, maintain, and optimize data pipelines from development to production for specific use cases.
Use innovative and modern tools, data services, techniques, and well architected frameworks to automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity.
Assist with optimizing the data management infrastructure to drive automation in data integration and management.
Implementing and using modern data preparation, integration and AI-enabled metadata management tools and techniques. Including MLOps framework and infrastructure automation.
Tracking data consumption patterns
Requirements
Bachelor's Degree in Computer Science/Engineering or equivalent experience preferred
The Data Engineer will build, manage and optimize data pipelines and move these data pipelines effectively into production for key data and analytics consumers like business/data analysts, data scientists or any business partner that needs curated data for data and analytics use cases across the enterprise.
Responsibilities
Create, maintain, and optimize data pipelines from development to production for specific use cases.
Use innovative and modern tools, data services, techniques, and well architected frameworks to automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity.
Assist with optimizing the data management infrastructure to drive automation in data integration and management.
Implementing and using modern data preparation, integration and AI-enabled metadata management tools and techniques. Including MLOps framework and infrastructure automation.
Tracking data consumption patterns
Requirements
Bachelor's Degree in Computer Science/Engineering or equivalent experience preferred
The Data Engineer will build, manage and optimize data pipelines and move these data pipelines effectively into production for key data and analytics consumers like business/data analysts, data scientists or any business partner that needs curated data for data and analytics use cases across the enterprise.
Responsibilities
Create, maintain, and optimize data pipelines from development to production for specific use cases.
Use innovative and modern tools, data services, techniques, and well architected frameworks to automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity.
Assist with optimizing the data management infrastructure to drive automation in data integration and management.
Implementing and using modern data preparation, integration and AI-enabled metadata management tools and techniques. Including MLOps framework and infrastructure automation.
Tracking data consumption patterns
Requirements
Bachelor's Degree in Computer Science/Engineering or equivalent experience
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