Senior Data Architect
$105k - $140kNutricia Nutrition Clinique SAS
Senior Bi Data Architect ManagerThe Senior BI Data Architect Manager acts as a subject matter expert in designing analytical approaches and leads the data-analytics teams in research, development, and implementation of appropriate data systems that lead to improved business performance and achievement of overall business goals. You will be responsible for developing and maintaining key critical data infrastructure encompassing SAP and other outside data sources into an active data eco system. This function will be supporting business data needs for tactical and strategic business initiatives and root cause analysis.Job Responsibilities:Engage with functional leaders to design, develop, and maintain dashboards supporting key KPIs and metrics and anticipate needs.Lead data architecture development to support evolving business data needs.Be the data partner to cross functional teams: Transportation, Warehousing, Planning, Operations, etc. work closely with IT for requirements, definitions and infrastructure development.Ingesting and transforming data from multiple sources, applying data quality checks, standardizing schemas, and integrating datasets at the appropriate grain to support accurate analytics and reportingEnforce data integrity and discipline in data policy and structure, one source of truth with one voice with wholistic and sync-ed data strategyTranslate data into actionable insights, strategies, and root cause analysisDevelop, maintain and enforce various taxonomies, hierarchies and structuresDevelop root cause reporting and tooling to engage the business and help deliver options while measuring the impact of those options.Seek to continuously raise the bar with data and impact.The salary range for this position is $105,000.00 -$140,000.00 USD. The exact salary offered will depend on several factors, including the candidate's relevant experience, geographic location, internal equity, and market conditions. Danone North America additionally offers a performance-based bonus and has a strong benefits package including Medical, Dental, Vision, Prescription Drug Coverage, 401k Plan, Wellness Program, Life Insurance, Tuition Reimbursement, Flexible Time Off, and Paid Parental Bonding Leave, among other benefit plan options. To give our employees flexibility, Danone is a hybrid work environment.This role is considered a "hybrid" position that allows for flexible work, meaning it is a role where collaboration with key stakeholders in Danone Hubs occurs. While you may have the option to work from home on a schedule as agreed to with your supervisor, you are also expected to regularly report to your assigned office location at least 3 days per week.Experience and Education Requirement:Master's degree in Supply Chain, Business Intelligence, Information Systems, Analytics, Computer Science, or related field with 8+ years of relevant experience.Business Acumen is crucial. Excellent communication, stakeholder management, and consulting skills, with the ability to translate business needs into technical solutions and technical concepts into business value.8+ years of SQL development experience across SQL Server, Oracle, Snowflake, or similar platforms.Proven track record on building data infrastructure, blending data, time series, datasets and tables for consumption.Knowledge, Skills and Abilities:Experience designing and building enterprise data warehouses, data lakes, and analytical data models for business consumption.Proven experience integrating, blending, and harmonizing SAP and external data sources into scalable data solutions.Experience with Databricks, Delta Lake, Python, and cloud-based data platforms preferred.Experience with Business Intelligence and visualization tools, including Power BI and Tableau.Strong knowledge of data architecture, data governance, master data management, hierarchies, taxonomies, and data quality frameworks.Proven ability to design flexible and scalable data structures that support evolving business requirements.Strong experience working with large datasets, data transformation, automation, and performance optimization.Demonstrated ability to influence cross-functional teams, establish standards, and drive adoption of enterprise data solutions.
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