Responsibilities:

• Create detailed solution design and reviews across relevant stakeholders to ensure alignment to the overall business needs including architecture overview, detailed solution architecture and documentations necessary the architecture decisions.
• Analyze, document, and optimize the overall solution architecture by developing design principles, models, plans, internal standards, budgets, and processes aligned on industry best practices.
• Provides technical oversight and recommendations on data infrastructure (on-premises and Cloud), Data Engineering and BI tool configuration to project teams.
• Participate in the selection of relevant technologies and products when solicited.
• Present and socialize proposed solutions to technical boards during review sessions as well as articulate and communicate designs to audiences with limited expertise related to the selected technology.
• Support the delivery of the solution by providing insights to the development teams and project managers that plan and execute delivery activities.
• Support implementation processes in association with internal and external development teams, participate in project-related activities and enforces guidelines and standards that production teams use to help guide their work.
• Assume responsibility for the quality of the implemented solution and its adherence to technology strategies, standards and best practices defined by the enterprise architecture team.
• Provide architectural leadership to development teams, and serve as the primary architect resource, and provide technical guidance and leadership to all internal and external teams involved in the implementation process.
• Create solution architecture documents that describe and explain solutions attributes and associated benefits and maintain documentation in collaboration with enterprise architects as well as others solution architects.
• Support the identification of opportunities for continuous improvement of solution management methodologies, including obtaining feedback after the solution has been implemented.
• Build standard solution templates for different business use cases.

Requirements & Skills:

• Bachelor’s degree in a related field (Information Technology, Engineering). An advanced degree in a related area, an asset.
• Minimum of 10 years of IT experience, of which minimum 5 as a solution experience working with integrated Enterprise systems
• Effective organizational skills with strong attention to detail for production of high-quality deliverables
• Having Snowflake certifications is must.
• Strong Knowledge of ETL/ELT frameworks using Snowflake, Talend, Azure Data Factory, and Databricks Notebooks(Pyspark).
• Strong knowledge in warehousing concepts and Snowflake based Enterprise Warehouse.
• Strong knowledge of Azure based architecture and services such as RBAC, AAD, VM, ADLS, Azure DevOps, Events hub.
• Knowledge of designing and implementing Gen AI based solutions specially on Snowflake.
• Highly advanced expertise with data manipulation and visualization tools such as Power BI.
• Must have some experience in at least one of the following RDBMS environments: MS SQL Server, Oracle.
• Expert knowledge of SQL and demonstrated ability to apply SQL creatively to a wide variety of business requirements.
• Strong Knowledge of ETL/ELT tools such as Talend or other as well as standards and best practices for ETL development.
• Knowledge on designing and implementing real time ingestion and processing framework.
• Proficient in building secure architecture using: Encryption, azure key vault, Access control, Network security, Advanced data security.
• Organizing and maintaining data processes to meet ongoing data warehouse lifecycle needs.
• Model the data using Dimensional Data Modelling, Data marts, Data Vault 2.0 modeling principles.
• Knowledge of Master Data and Reference Data concepts and solutions
• Knowledge of Big Data concepts, Cloud Solutions such as Azure.
• Good knowledge of Data Governance principles & tools such as Collibra.
• Strong analytical, decision-making skills and demonstrated ability to learn new tools and systems.
• Knowledge in APIs, web services concepts, standards and JSON, XML, XML Schema.
• Experience in designing and implementing large data workloads with particular attention to security, scalability, and high performance.
• Ability to work across multiple technical teams to set direction and priority.
• Ability to work independently and as part of a team while demonstrating initiative and using good business acumen.
• Ability to motivate and integrate team members, Team player with effective interpersonal skills.
• Experience working within multidisciplinary and collaborative environments.

The post Solution Architect – Data & Analytics, Air Canada appeared first on AI Jobs Latest.

Responsibilities:

• Be a data visualization and analytics thought partner to leadership defining and implementing a data visualization strategy and center of excellence aligned to business goals.
• Oversee end-to-end development lifecycle of reporting solutions (e.g. interactive dashboards, general reporting templates) ensuring quality, accuracy and scalability.
• Evaluate and recommend modern technologies (e.g. natural language queries) to enhance reporting capabilities on structured data sets for faster time to insight.
• Create a clear implementation process, while managing capacity and timelines ensuring successful delivery.
• Lead and mentor a growing team of BI / Data Visualization Developers providing guidance in code review, UI/UX best practices and iterative dashboard development.
• Champion a data culture of self-service driving continuous reporting solution adoption with stakeholders through user-friendly features.

Requirements & Skills:

• You have 5 – 7+ years of experience as a BI Developer/Analyst / Analytics Engineer developing scalable reporting dashboards in Power BI, Tableau, and/or other visualization tools.
• You have 5+ years of managing a team of BI developers, analytics engineers, or analysts in an agile / Scrum environment and a demonstrated history of steering reporting solution initiatives cross-functionally with success.
• You have experience collaborating with business stakeholders, impacting decision-making processes, providing business improvement recommendations, and data/visualization storytelling.
• You have a proven ability to develop SQL/SparkSQL and experience in modern cloud-based data warehouses, as well as a strong understanding of large event-based data sets and diverse schemas.
• You have experience implementing natural language queries (NLQs) into dashboards, increasing data literacy and adoption across the organization.
• You have an exceptional understanding of UI/UX best practices with a keen eye for visual design and attention to detail.
• You have a strong sense of business acumen and strategic thinking.
• You have strong interpersonal skills communicating with technical and non-technical audiences and can build relationships outside of your team reporting structure.
• You have experience translating business stakeholder needs into technical design documentation.
• You have a direct-to-consumer background or history of working in subscription services.

The post Sr. Manager – BI & Data Visualization, McAfee appeared first on AI Jobs Latest.

Responsibilities:

• Develop innovative solutions using machine learning and advanced statistics to solve business problems.
• Influence the AI roadmap of the biggest P&C insurer in Canada.
• Keep pace with new approaches and trends and use them in your own solutions.
• Work within a multi-disciplinary environment mixing people from data science, software engineering, actuarial science, business and design.
• Share knowledge with interns and other data scientist to grow, as a team All this, while keeping a good work-life balance.

Requirements & Skills:

• A bachelor’s degree in a quantitative discipline such as mathematics, science, engineering, statistics, AI, computer science, or a related field. MSc and/or PhD are an asset.
• 2+ years of experience in the field of data science, machine learning, and advanced statistics solving business problems.
• Programming experience in languages such as Python or R as well as knowledge of software engineering best practice or a strong desire to learn it.
• Familiar with the underlying theory of machine learning (supervised, unsupervised,d and reinforcement learning).
• The commitment to be a great, collaborative teammate.
• Unlimited curiosity and a passion to challenge the status quo.
• Ability to focus on vaguely defined issues requiring the application of a creative approach.
• Strong communication, time management, and work organization skills.

The post Data Scientist, Intact Lab appeared first on AI Jobs Latest.

Responsibilities:

• Data Analysis and Modeling. Utilize statistical methods and machine learning algorithms to analyze complex data sets, build predictive models, and derive actionable insights.
• Data Visualization and Communication. Create clear and compelling data visualizations and reports to effectively communicate findings and recommendations to stakeholders.
• Collaboration and Strategy Development. Work with cross-functional teams to integrate data science solutions into business strategies, providing expertise in data-driven decision-making and innovation.

The post Data Scientist, NTT DATA appeared first on AI Jobs Latest.

Responsibilities:

• Drive the development of products and platforms with a focus on Machine Learning and Data Engineering.
• Design secure, reliable, and scalable solutions that incorporate both functional and non-functional requirements from product teams, security teams, and technology stakeholders. Present these solutions for review within Loyalty Products and to the wider Mastercard Architecture & Technology Architecture Review Team.
• Define the technical strategy for Loyalty Data and Predictive Analytics, contributing to long-term goals, roadmaps (12-18 months), and detailed planning at quarterly and sprint levels.
• Lead modernization efforts and data transformation solutions for Loyalty Data products, ensuring compliance with payment standards and regulations like PCI-DSS, GDPR, and local On-Soil requirements.
• Collaborate with technical leads, data stewards, DBAs, and database developers to support large-scale, like-for-like data migrations.
• Stay informed about emerging trends and best practices in big data and cloud platforms, providing technical leadership to enhance the quality of data platforms continuously.
• Work closely with teams like Data Privacy, Information Security, Cryptographic Architecture, and Business Operations to gather requirements and ensure compliance with Mastercard policies, industry standards, and regulations.
• Translate business requirements into technical specifications involving data streams, integrations, transformations, databases, and data warehouses.
• Define the framework, standards, and principles for data architecture, covering areas such as modeling, metadata, security, and reference data.
• Evaluate and recommend the best analytics solutions, considering usability, technical feasibility, timelines, and stakeholder needs.
• Break down large solutions into smaller, achievable milestones to gather feedback and data from product managers and stakeholders.

Requirements & Skills:

• Expertise in data platform engineering concepts, architecture design patterns, and industry best practices.
• Subject matter expertise in Databricks and experience in cloud infrastructure, particularly AWS and/or Azure.
• Advanced statistical analysis, coding, and data engineering techniques.
• Open-source tools, predictive analytics, machine learning, and advanced statistics for basic analytical tasks.
• Proficiency in Python, Scala, Spark, Hadoop platforms and tools (Hive, Impala, Airflow, NiFi, Sqoop), and SQL to build Big Data products and platforms.
• Experience developing and deploying production-level data applications and workflows/pipelines, including machine learning systems in Java, Scala, or Python, with full lifecycle involvement—from data ingestion to feature engineering, modeling, and evaluation.
• Architecting scalable data migration solutions using cloud and data lake technologies, along with data transformation tools like Airflow and NiFi for data pipeline orchestration and SQL Server SSIS for ETL.
• Cloud security models, encryption strategies, and network layers for hybrid on-prem and cloud environments.
• Curiosity, creativity, and enthusiasm for technology and innovation.
• Strong quantitative and problem-solving skills.
• An ability to multitask with attention to detail.
• Self-motivation, flexibility, and independence in managing your workload.

The post Principal Big Data Engineer, Mastercard appeared first on AI Jobs Latest.

Responsibilities:

• Design, develop, optimize, and maintain data architecture and pipelines for analyzing large data sets and identifying patterns and relationships.
• Solve complex data problems to deliver insights that help the organization achieve its goals
• Manage data sources, organize data, and create data assets using identified open-source or proprietary tools
• Design and implement cloud security and access control mechanisms to protect the data from unauthorized use
• Interact with other technology teams to define, prioritize, and ensure smooth deployments for other operational components.
• Advise, consult, mentor, and coach other data and analytics professionals on data standards and practices.
• Foster a culture of sharing, reuse, design for scale stability, and operational efficiency of data and analytical solutions.
• Codify best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases to facilitate data capturing and management.
• Code in SQL to create curated data products.

Requirements & Skills:

• Bachelor’s degree in any of the following – Engineering, Computer Science or other technical field
• Minimum 6 years of relevant experience in data engineering/analytics space
• Experience developing solutions for cloud computing services, cloud security, and infrastructure on AWS and/or Azure
• Experience developing solutions on cloud services like SageMaker, EC2, S3, EMR, Redshift, IAM, etc.
• Experience developing and maintaining data warehouses in big data solutions
• Expertise in SQL and data analysis and strong hands-on expertise with at least one programming language: Python and/or Scala
• Strong knowledge in one or more of the following big data tools: Spark, Hive
• Strong expertise in ETL, reporting tools, data governance, data warehousing, and hands-on experience
• Up-to-date on industry trends within the analytics space from a data acquisition processing, engineering, and management perspective
• Strong people skills, specifically in collaboration and teamwork
• High level of curiosity, creativity, and problem-solving capabilities

The post Data Engineer, Abbott appeared first on AI Jobs Latest.