Niveau: Mid-Senior level
Type d’emploi: Full-time
le contenu du travail
Data Architect Consultant
Location: Toronto, ON
We Are:
Applied Intelligence, the people who love using data to tell a story. We’re also the world’s largest team of data scientists, data engineers, and experts in machine learning and AI. A great day for us? Solving big problems using the latest tech, serious brain power, and deep knowledge of just about every industry. We believe a mix of data, analytics, automation, and responsible AI can do almost anything—spark digital metamorphoses, widen the range of what humans can do, and breathe life into smart products and services. Want to join our crew of sharp analytical minds? Visit us here to find out more about Applied Intelligence.
You are:
A hands-on Solution Architect who knows how to develop, design and maintain technologies that work for our clients. You are a next-generation thinker when it comes to what we call Data in the New. Your superpower? Using the latest data and analytics technologies to help clients glean the most value from their data. And you know how to come up with strategies, solutions, and processes for managing enterprise-wide data throughout the data life cycle. You’re a digital native who’s right at home when the challenge calls for teamwork and originality
The work:
Defining the policies & standards for cloud native data management for structured, semi- and unstructured data use
Defining the data architecture for cloud native data management with expert level knowledge on
Popular Cloud Platforms (e.g. AWS, Azure, GCP)
Data Layers (e.g. raw, curated)
Integration design (e.g. APIs), ETL (Extract, Transform & Load), velocity (e.g. streaming)
Data architecture design patterns
Defining the data architecture for cloud native data management with focus to
Business process flows to support data sourcing & lineage
Data Modelling methodologies & tools
Reference Architectures
Defining the data architecture for cloud native data management with focus to
(Business) Data Definitions & Metadata
Reference Data Management
Master Data Management (core & critical business data entities)
Data Lineage
Defining the data management vision & strategies, managing the change journey and/or playing serving as the “architect” to design and scale end to end data management with special focus to
Data Quality Rules & KPIs
Automated Data Cleansing (e.g. use of AI / ML)
Compliance Rules & KPIs
Data democratisation
Data security
Compliance & security policies for data access, use & integration
Qualifications - External
Here’s What You Need:
A minimum of 3 years of working as a Data Governance consultant or directly with clients leveraging popular tools like Informatica, Collibra, IBM, ASG etc.
A minimum of 3 years in a role that had taken ownership of the data assets for the organization to provide users with high-quality data that is accessible in a consistent manner.
A minimum of 3 years facilitating Data cleansing and enrichment through data de-duplication and construction
A minimum of 3 years in a role that discovered captures the current state of the system, encompassing processes such as data discovery, profiling, inventories.
A minimum of 3 years in a role that defined processes include data classification, business glossary creation and business rule definition.
A minimum of 3 years in a role that applied processes with aim to operationalize and ensure compliance with policies and include automating rules, workflows, collaboration etc.
Bonus Points if:
Experience in a role that led measurement and monitoring to determine the value generated and include impact analysis, data lineage, proactive monitoring, operational dashboards and business value.
Experience in a role that led repeatable, iterative, and standardized processes to define how the data should be governed. At a minimum, below processes and procedures must have been practiced
Defining data domains
Change Management
Data stewardship and ownership
Conflict resolution
Technology Automation
Communication
Experience performing:
Master Data Management
Metadata Management
Data Management and Integration
Systems Development Lifecycle (SDLC)
Data Modeling Techniques and Methodologies
Database Management
Database Technical Design and Build
Extract Transform & Load (ETL) Tools
Cloud Data Architecture, Data Architecture Principle
Online Analytical Processing (OLAP)
Data Processes
Data Architecture Principles
Data Architecture Estimation
Date limite: 27-07-2024
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