Posted:1 day ago|
Platform:
On-site
Contractual
Our client is founded in 2002 with offices in the US, India, Europe, Canada, Singapore, Costa Rica, Brazil, and the UK they got national and international scope and reach, backed by decades of experience and deep domain expertise. They specialize in Products such as AI Governance/Data Privacy and Services such as Interactive (Product, Discovery, Research, User Journey, Prototyping), Talent, Cloud (Development, Transformation, SRE, Architecture), Engineering (Web, Mobile, Strategy), Enterprise (Salesforce, ServiceNow, SAP, Oracle, Microsoft, Workday), Training (Corporate Learning Design and Development), and building offshore cost-effective captive Global Capability Centers.
· Design and optimize data pipelines that integrate various data sources (1st party, 3rd party, operational) to support business intelligence and advanced analytics.
· Develop data models and data flows that enable personalized customer experiences and support omnichannel marketing and customer engagement.
· Lead efforts to ensure data governance, data quality, and data security, adhering to compliance with regulations such as GDPR and CCPA.
· Implement and maintain data warehousing solutions in Snowflake to handle large-scale data processing and analytics needs.
· Optimize workflows to streamline data transformation and modeling processes.
· Leverage Azure for cloud infrastructure, data storage, and real-time data analytics, while ensuring the architecture supports scalability and performance.
· Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders, to ensure data architectures meet business needs.
· Support both real-time and batch data integration, ensuring data is accessible for actionable insights and decision-making.
· Continuously assess and integrate new data technologies and methodologies to enhance the organization’s data capabilities.
· 4+ years of experience in Data Architecture or Data Engineering, with specific expertise in, Snowflake, and Azure.
· Strong understanding of data modeling, ETL/ELT processes, and modern data architecture frameworks.
· Experience designing scalable data architectures for personalization and customer analytics across marketing, sales, and customer service domains.
· Expertise with cloud data platforms (Azure preferred) and Big Data technologies for large-scale data processing.
· Hands-on experience with Python for data engineering tasks and scripting.
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