Montréal,

Data Architecture Innovation Principal Director

Location: Toronto/Ottawa/Montreal

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 Accenture Applied Intelligence

You are:

As a Digital Data Innovation Principal Director in our practice you will help shape and sell industry specific programs, including definition of the analytics/AI vision and strategies, redefine operating model and talent strategy, and help guide clients through their data and analytics journeys to deliver sustainable business value. You will act as the architect for our most transformative opportunities, enabling an end-to-end analytics journey by bringing the best of our Accenture Applied Intelligence organization. You will also play a key role on the leadership team – building a practice, assets, and thought leadership.

The work:

Defining the data architecture for cloud native data management for structured, semi- and unstructured data use

Leading high impact data strategies (why, how, value, and approach) for our client’s senior leadership in their data organization (SVP to C-suite); leading small teams of motivated generalists and deep specialists

Being a day-to-day leader and client relationship management of diverse delivery teams working with mid-level clients

Acting as knowledgeable expert in data management and engineering to advise clients and Accenture teams as a subject matter advisor

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

Here’s what you need:

+ 8 to 12 years working as a consultant or directly with clients

+ 8 to 12 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.

+ 8 to 12 years facilitating Data cleansing and enrichment through data de-duplication and construction

+ 8 to 12 years in a role that discovered captures the current state of the system, encompassing processes such as data discovery, profiling, inventories.

+ Defining the policies & standards for cloud native data management for structured, semi- and unstructured data use

+ 8 to 12 years in a role that defined the data architecture for cloud native data management with expert level knowledge on

+ At least one popular Cloud Platforms (AWS or Azure or GCP)

+ Data Layers (e.g. raw, curated)

+ Integration design (e.g. APIs), ETL (Extract, Transform & Load), velocity (e.g. streaming)

+ Data architecture design patterns

+ 8 to 12 years in a role that defined 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

+ 8 to 12 years in a role that defined 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

+ 8 to 12 years in a role that defined, 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

+ 8 to 12 years performing ad-hoc Data extraction and archival; Managing Data life-cycle.

+ Experienced in Data Storage Tools & Techniques, Data Archiving Patterns & Techniques, Cloud Backup Architecture and Design, Data Warehouse Tools, Data Conversion & Migration, Master Data Management, Metadata Management, Network Data Management Protocol (NDMP), Informatica MDM, 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 Principles, SAS DataFlux ETL Tools, Online Analytical Processing (OLAP), Data Processes, Data Architecture Principles, Data Architecture Estimation

Bonus points if:

+ Expertise in using Hadoop, MapReduce, Spark, Pig, Hive technologies, Data Ingestion in Data Lake, Data Storage on key Cloud providers (AWS, Azure, GCP), Redshift, Data Retrieval on Big Data platforms and Interfacing Data Science and Data Visualization tools on Big Data platforms

+ Experience in Data Modeling, Big Data Platforms (e.g. Cloudera, Hortonworks, AWS, Talend, etc.), Data Migration and Quality (using ETL e.g Informatica), MySQL/NoSQL, CQRS Event Sourcing

Montréal,

Accenture is a global management consulting, technology services and outsourcing company. Combining unparalleled experience, comprehensive capabilities across all industries and business functions, and extensive research on the world’s most successful companies, Accenture collaborates with its clients to help them become high-performance businesses and governments.

Working with Accenture in the United States,  you can join ranks with more than 211,000 people in 120 countries and work with clients in nearly every major industry worldwide, including 96 of the Fortune Global 100, more than three-quarters of the Fortune Global 500 and government agencies around the world. Accenture’s people build careers in different areas of business, specifically Consulting, Technology and Outsourcing, as well as within our internal corporate functions.

With the breadth of talent our people have, they not only build strong careers, they offer their talents and skills to help clients and communities around the world.

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