Data Architecture Innovation Principal Director

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