Data Warehouse Architect

2i Solutions, Inc; Hamilton; On-site; CAD 90,000 - 130,000; Full time

Job summary

2i Solutions, Inc. is seeking a Data Warehouse Architect for a 6-month contract in Hamilton, Ontario.

The ideal candidate will be passionate about system architecture, big-data processing, data modelling, advanced quantitative models, data visualization, and performance optimization in large-scale databases. You will develop conceptual, logical, and physical data models for an Enterprise Data Warehouse, define ETL standards and test plans, and design robust data pipelines to support near

Qualifications

• Enthusiastic about system architecture and large-scale data processing.
• Experience with data modelling and quantitative data-driven models.
• Knowledge of data visualization and performance optimization for big data.

Responsibilities

• Develop conceptual, logical, and physical data models for an Enterprise Data Warehouse.
• Define ETL processes, design standards, and test plans for the Enterprise Data Warehouse.
• Build scalable data solutions and pipelines to automate ingestion, processing and delivery of data.
• Ensure alignment with target state data architecture and data management standards.
• Assist in selecting data management tools required to expand platform capabilities.

Skills

System architecture

Big-data processing

Data modelling

Data visualization

Performance optimization

Job description

There is a 6 months contract opportunity for Data Warehouse Architect in Hamilton, Ontario.

Candidate must be enthusiastic about system architecture, big-data processing, data modelling,

advanced quantitative data-driven models, data visualization, and performance optimization in large scale databases.

Develop conceptual, logical, and physical data models as part of an Enterprise Data Warehouse.

Develop design standards, naming conventions, ETL processes, and test plans for the Enterprise Data Warehouse.

Standard working day is equal to 7.5 Hours.

Candidates will be expected to work onsite in Hamilton, Ontario, Canada at locations designated by HHSC from time to time;

1.0 The Digital Health Plan: Data, Analytics & Planning project is a multi-year program to invest in Hamilton Health Science’s (HHS) data and analytics capabilities.

Our project team will build and operate an Enterprise Data Warehouse that integrates data from dozens of different source systems and implement a leading analytics platform for data visualization.

These tools will help HHS harness our data to make smarter decisions about how we serve our patients and how we operate our hospital system.

2.0 This agile data architecture and integration project is fast paced, collaborative and highly technical: team members will model and integrate data from dozens of systems then create complex quantitative models and high caliber visualizations in support of decision making.

Candidate Description

Candidate must be enthusiastic about system architecture, big-data processing, data modelling, advanced quantitative data-driven models, data visualization, and performance optimization in large scale databases. Candidate can envision, and lead a team to implement architectures for high volume near-real-time ingestion, transformation and visualization of data while ensuring data quality, broad accessibility and high security, all while protecting the privacy of our most important stakeholders – our patients.

The prospect of working with large volumes of healthcare data is an ideal position for the candidate .

Specific types of deliverables for this engagement will be

3.0 Develop conceptual, logical, and physical data models as part of an Enterprise Data Warehouse unifying administrative and clinical systems. The overall model should consider all source systems, but will focus on key areas initially such as Lab, Pharmacy, Patient Demographics, General Ledger;

4.0 Develop design standards, naming conventions, ETL processes, and test plans for the Enterprise Data Warehouse;

5.0 Design robust, reusable and scalable data solutions and pipeline frameworks to automate ingestion, processing and delivery of batch and real-time streaming data;

6.0 Ensure on-going alignment of new and existing data initiatives with the target state data architecture;

7.0 Define standards and best practices for enterprise data management framework;

8.0 Play an active role in all stages of a data solution life cycle: acquisition, ingestion, curation, publication, quality and metadata to ensure consistency with data management standards and best practices; and

9.0 Assist in the selection of data management tools required to expand our platform capability.