Data Arch Senior Manager

Data Architect Sr Manager

Location: Toronto

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 curious leader who can connect and advise senior clients with storytelling and strong data driven mindset. As a manager, you will be a coach to develop our up and coming leaders in their careers, and a day to day leader of our diverse multi-disciplinary workforces to solve our client’s data challenges.

As a Data Architecture Senior Manager, you will apply deep delivery acumen for data driven engagements, architecting value, and operating model architecture skills to influence client agendas through business insight in a data driven reinvention and culture.  You will partner with our clients to make bold decisions on priority C-Suite issues at the intersection of business, technology, and operations within a complex data management landscape.

You will provide deep understanding of our clients' industry landscape and options to mature data management practice from people, process, and technology in the context of global, economic, technology and social trends.

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