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Data Analytics Technical Lead

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Logo of Allwyn Corporation

Allwyn Corporation

51 - 200 employees

Founded 2003

đŸ€– Artificial Intelligence

🏱 Enterprise

đŸ€ B2B

Artificial Intelligence ‱ Enterprise ‱ B2B

Allwyn Corporation is a US-headquartered technology consulting and services firm focused on helping organizations modernize IT and leverage data to drive operational efficiency. The company offers AI & Machine Learning, data analytics and business intelligence, enterprise applications, IT modernization, agile software delivery, low-code development, offshore delivery, and SATCOM engineering services. Allwyn positions itself as a partner for public-sector and utility leaders seeking digital transformation and cites customer success (e. g. , IBTS) for modernizing government-facing applications. Headquarters are in Herndon, VA with offices in New York and an offshore delivery center in Hyderabad, India.

📋 Description

‱ Lead enterprise-scale analytics initiatives ‱ Design and deliver end-to-end analytics and data engineering solutions ‱ Collaborate with cross-functional teams to ensure alignment with business objectives ‱ Optimize ETL/ELT pipelines for performance and scalability ‱ Manage and mentor analytics and engineering teams ‱ Implement best practices in data governance and CI/CD DevOps processes

🎯 Requirements

‱ Extensive hands-on experience in Databricks ‱ Advanced data engineering and lakehouse architecture ‱ Performance optimization supported by relevant Databricks certifications ‱ Leading enterprise-scale analytics initiatives across cloud and big data platforms ‱ Strong background in AI/ML solutions and predictive analytics ‱ Experience with data warehousing and ETL/ELT modernization ‱ Proficiency in business intelligence and visualization tools like Power BI and Tableau ‱ Strong knowledge of cloud platforms, primarily AWS ‱ Expertise in real-time and batch data processing frameworks ‱ Strong leadership experience in managing and mentoring cross-functional teams ‱ Ability to deliver actionable insights and enterprise data transformation outcomes ‱ Designing and delivering analytics and data engineering solutions ‱ Building and optimizing ETL/ELT pipelines within modern lakehouse architectures ‱ Hands-on implementation of secure, high-performance cloud data platforms ‱ Focus on data quality, governance, lineage, observability, and CI/CD practices ‱ Advanced knowledge of Databricks capabilities including Delta Live Tables, Unity Catalog, and performance tuning of distributed Spark workloads ‱ Mentoring engineering teams and establishing best practices

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