Data Analytics Technical Lead

🕒 July 30

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Logo of Allwyn Corporation

Allwyn Corporation

51 - 200 employees

Founded 2003

🤖 Artificial Intelligence

🏢 Enterprise

🤝 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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