Cognite Solution Lead

Job Description

Infosys is seeking a lead Data Architect/Cognite Solution in Calgary, Canada. Infosys is a global leader in technology services and consulting. We enable clients in more than 50 countries to create and execute strategies for their digital transformation. Our team of 190,000+ innovators, across the globe, is differentiated by the imagination, knowledge, and experience we bring to every project we undertake.

Location: Calgary, Canada. This position may require 10% travel.

Qualifications Basic:

1. Bachelor's degree or foreign equivalent required from an accredited institution.
2. Candidates authorized to work for any employer in Canada without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time.

Key Words:

Cognite Data Fusion, Cognite, Data Architect, Data Bricks, Azure Data Factory.

Mandatory Skills:

1. At least 10~12 years of experience in data modeling, data engineering, data governance, advanced analytics with domain knowledge and exposure to industrial sectors such as Energy, Manufacturing, Petro-chemicals, Oil & Gas.
2. Working knowledge in the Industrial Data platform and Engineering Analytics tools such as Cognite Data Fusion [CDF], Azure Data Factory, Azure Databricks, Azure Data Lake.
3. Independently manage integration, data modeling, and related activities using Cognite tools (connectors, SQL, Python/Java, Rest APIs).
4. Define enterprise and solution architecture, including integration, data models, and data pipelines using CDF solution offerings.
5. Knowledge of Cognite Infield and Maintain or any other relevant platform.
6. Understanding of CDF architecture, components, data modeling capabilities, data ingestion and transformation features, data visualization and analysis tools.
7. Proven experience in designing and implementing applications that leverage maintenance, production, and process data.
8. Strong skills in ETL processes, data integration tools, techniques, and data pipelines.
9. Proficiency in languages such as Python and SQL for scripting, automation, and querying data within the data platform.
10. Experience working with REST APIs to integrate external data sources with the data platform.
11. Knowledge in defining the data requirements and structure for the application.
12. Experience in data modeling and designing the application data structure, storage, and integration.
13. Familiarity with applying ML models, Gen AI Tech stack, LLM skills, AI and analytics with the data platform environment.
14. Knowledge of different sources of data such as SAP data, Production and Operation data, Time series data, Engineering data.
15. Understanding of industry standards (ISA 95 and Industry 4.0) and maintenance strategies of any manufacturing or industry sector.
16. Knowledge in application development, architectural frameworks, SDLC methodologies including Design, Development, Integration, Testing, Security, Access, and others.
17. Familiarity with Network Topology, Database Server, Hosting components, Industrial communication protocols, etc.
18. Good communication and coordination skills with internal and external stakeholders.
19. Ability to lead and mentor Data Engineers, Development, and Testing teams.

The job entails sitting as well as working at a computer for extended periods of time. Should be able to communicate by telephone, email, or face to face.