AI Analytics and Visualization Engineer

Consultant, Data Analytics & Reporting-Food

Senior Data Engineer

Associate Data Engineer

Role Description: <ul><li>The AI Analytics &amp; Value Realization Engineer is responsible for ensuring AI initiatives deliver measurable business value across ICT Engineering.</li><li>The role establishes value measurement frameworks, validates benefits, develops performance dashboards, and enables data-driven decision making across the AI portfolio. This position serves as the primary subject-matter expert for AI adoption measurement, business impact reporting, value realization tracking, and portfolio analytics</li></ul> Responsibilities: Value Definition &amp; Business Case Support <ul><li>Partner with AI Transformation Engineers during opportunity assessments.</li><li>Establish baseline metrics, value hypotheses, and expected business outcomes.</li><li>Define standardized measurement methodologies and evidence requirements for AI initiatives, distinguishing between forecast, validated, realized, and sustained business value.</li><li>Develop approaches for measuring engineering productivity and operational benefits, including time savings, cycle-time reduction, quality improvement, throughput, and adoption where direct financial measurement is not feasible.</li><li>Challenge assumptions and ensure value estimates are fact-based and measurable.</li></ul> Portfolio Measurement &amp; Reporting <ul><li>Develop and maintain AI portfolio dashboards and KPI reporting.</li><li>Track solution adoption, utilization, and business impact.</li><li>Collect and analyze deployment performance data.</li><li>Ensure consistent reporting across all AI initiatives.</li><li>Generate monthly reporting for ICT Engineering leadership, ICT AI leadership, and segment AI leadership.</li></ul> Value Realization &amp; Validation <ul><li>Validate achievement of project objectives and business benefits.</li><li>Monitor sustainability of realized benefits after deployment.</li><li>Identify underperforming initiatives and recommend corrective actions.</li><li>Support prioritization decisions using objective performance and value data.</li><li>Develop standardized value realization methodologies and reporting processes.</li><li>Design measurement approaches that compare pre- and post-deployment performance and provide credible evidence that observed improvements are attributable to deployed solutions.</li></ul> Advanced Analytics <ul><li>Perform portfolio analytics and trend analysis.</li><li>Support executive decision-making with actionable insights.</li><li>Maintain data quality and governance standards for AI program reporting.</li><li>Build Power BI dashboards and reporting solutions.</li></ul> Requirements: Experience &amp; Qualifications <ul><li>Bachelors degree in Engineering, Data Analytics, Business Analytics, Statistics, or related field.</li><li>Experience with analytics and visualization tools such as Power BI, including dashboard development, KPI reporting, and data analysis.</li><li>Strong analytical and quantitative problem-solving skills.</li><li>Experience developing and maintaining business metrics and measurement frameworks.</li><li>Experience establishing performance baselines and designing measurement approaches to evaluate the impact of implemented solutions.</li><li>Ability to translate complex data into actionable business insights.</li><li>Knowledge of engineering, technology, or transformation programs preferred.</li><li>Strong communication and executive presentation skills.</li></ul>

Responsibilities: <ul><li>Data Analysis: Collects, transforms, and analyzes data from multiple sources to identify trends, patterns, anomalies, and actionable insights that support reporting, performance tracking, and decision making.</li><li>Reporting &amp; Visualization: Implements detailed reports and dashboards using various tools, designs and completes data visualizations to communicate moderately complex data clearly.</li><li>Data Modeling &amp; Automation: Supports data models, reporting logic, and workflow automation, while identifying and implementing opportunities to improve data collection and reporting processes using standard data management and reporting practices.</li><li>Advanced Analytics Awareness: Familiarity with predictive analytics, AI/ML, and data science concepts to support evolving analytics solutions.</li><li>Data Quality &amp; Requirement Support: Validates data, supports reporting requirements, and helps ensure the accuracy and consistency of analytics solutions.</li></ul> Requirements: <ul><li>Bachelor’s degree in a related field such as Data Science, Statistics, Computer Science, Business Analytics, or a related discipline, or equivalent practical experience.&nbsp;</li><li>Minimum of 3-4 years of relevant work experience in data analytics, reporting, or business intelligence roles.</li><li>Strong skills in analyzing data and translating reporting needs into effective analytics solutions and insights.</li><li>Very strong skills in Power BI and data visualization.</li><li>Proficiency in SQL, Excel, Power Query, and related tools such as VBA or Python for analysis, modelling, and visualization.</li><li>Working knowledge of data warehousing, data lakes, and cloud data platforms such as Snowflake or AWS.</li><li>Experience automating workflows and building low-code solutions using Power Platform tools such as Power Automate and Power Apps.</li><li>Familiarity with (predictive) analytics, AI/ML and data science.</li><li>Business understanding and financial acumen to interpret data and generate practical insights.</li><li>Comfortable working in agile ways of working, managing multiple priorities, and contributing effectively both independently and in a team environment.</li></ul>

Responsibilities: Data Infrastructure:&nbsp; <ul><li>Prepares data infrastructure to support the efficient storage and retrieval of data.</li></ul> Data Formats:&nbsp; <ul><li>Examines and resolves appropriate data formats to improve data usability and accessibility across the organization.</li></ul> Data &amp; Analytical Solutions:&nbsp;&nbsp; <ul><li>Develops complex data products and solutions using advanced engineering and cloud based technologies, ensuring they are designed and built to be scalable, sustainable and robust.</li></ul> Data Pipelines:&nbsp;&nbsp; <ul><li>Develops and maintains streaming and batch data pipelines that facilitate the seamless ingestion of data from various data sources, transform the data into information and move to data stores like data lake, data warehouse and others.</li></ul> Data Systems:&nbsp;&nbsp; <ul><li>Reviews existing data systems and architectures to identify areas for improvement and optimization.</li></ul> Stakeholder Management: <ul><li>Collaborates with multi-functional data and advanced analytic teams as well as with business teams to gain requirements and ensure that data solutions meet the functional and non-functional needs of various partners.</li></ul> Data Frameworks:&nbsp; <ul><li>Builds complex prototypes to test new concepts and implements data engineering frameworks and architectures that improve data processing capabilities and support advanced analytics initiatives.</li></ul> Automated Deployment Pipelines:&nbsp;&nbsp; <ul><li>Develops automated deployment pipelines improving efficiency of code deployments with fit for purpose governance.</li></ul> Data Modeling:&nbsp;&nbsp; <ul><li>Performs complex data modeling in accordance to the datastore technology to ensure sustainable performance and accessibility.</li></ul> Requirements: <ul><li>Minimum requirement of 4 years of relevant work experience.&nbsp;</li><li>Typically reflects 5 years or more of relevant experience.</li></ul>

Responsibilities: <ul><li>Ability to troubleshoot problems in a live environment and provide real time help with critical issues.</li><li>Write code that is easily understood and maintainable by other team members.</li><li>Keep up to date with developments in technologies we are using.</li><li>Ability to communicate and work effectively, supporting various business departments.</li><li>Ability to work in fast-paced interdisciplinary environment.</li></ul> Requirements <ul><li>BA/BS in Computer Science or equivalent practical experience.&nbsp;</li><li>At least 3+ years of post-university experience as a full-stack engineer.</li><li>Solid knowledge of programming fundamentals—algorithms, data structures, design patterns, and paradigms.</li><li>Strong knowledge of Python.</li><li>Solid knowledge SQL and relational databases.</li><li>Knowledge of Extract-Transform-Load (ETL) and big data analytics tools.</li><li>Experience working in a cloud environment (AWS, Azure, GCP).</li><li>Familiarity with popular Python data analytics frameworks.</li><li>Familiarity with Snowflake or other large analytics engines.</li><li>Experience with data warehousing and working in environments with large scale, complex analytics requirements.</li><li>Familiarity with DAG-based job scheduling tools.</li><li>Cloud-native container orchestration platforms and tools.</li><li>Experience working in the Financial Services industry.</li></ul>

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AI Analytics and Visualization Engineer

Consultant, Data Analytics & Reporting-Food

Senior Data Engineer

Associate Data Engineer

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AI Analytics and Visualization Engineer

Consultant, Data Analytics & Reporting-Food

Senior Data Engineer

Associate Data Engineer

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