Posted Apr 4, 2026
As a Data Engineering & AI Practice Leader, your role will involve overseeing the strategic direction and operations of the Data & AI practice. With over 20 years of experience in data engineering and analytics/AI leadership, you will be responsible for driving revenue growth, profitability, and successful delivery of complex data and AI solutions at scale. Key Responsibilities:
Define and execute the Data & AI practice roadmap, focusing on revenue recognition, profitability, and growth. - Lead pre-sales activities, RFP responses, and solutioning for large-scale data platforms and AI initiatives. - Provide guidance on architecture, warehousing, pipelines, governance, and cloud-native platforms such as AWS, Azure, and GCP. - Champion emerging technologies like Agentic AI and advanced automation to drive innovation. - Build and manage strategic vendor and industry alliances to enhance partnerships. - Ensure delivery excellence by overseeing project execution with high quality, on-time, and on-budget outcomes. - Mentor and develop a high-performing team of data engineers, scientists, and AI specialists. Qualifications:
Minimum of 20 years of experience in data engineering, with a background in data warehousing and expertise in analytics/AI practice leadership. - Track record of designing and managing modern data platforms like Snowflake, Databricks, BigQuery, and Redshift. - Strong understanding of AI/ML concepts and their business applications. - Demonstrated proficiency in revenue recognition, profitability management, and practice P&L ownership. - Experience in establishing strategic partnerships and collaborating on go-to-market strategies. - Advanced technical skills in Spark, ETL/ELT processes, SQL/NoSQL databases, and data governance. - Excellent leadership abilities, effective communication skills, and adept stakeholder management. - Bachelors or Masters degree in Computer Science or Engineering; MBA qualification is preferred. This job description does not contain any additional details about the company. As a Data Engineering & AI Practice Leader, your role will involve overseeing the strategic direction and operations of the Data & AI practice. With over 20 years of experience in data engineering and analytics/AI leadership, you will be responsible for driving revenue growth, profitability, and successful delivery of complex data and AI solutions at scale. Key Responsibilities:
Define and execute the Data & AI practice roadmap, focusing on revenue recognition, profitability, and growth. - Lead pre-sales activities, RFP responses, and solutioning for large-scale data platforms and AI initiatives. - Provide guidance on architecture, warehousing, pipelines, governance, and cloud-native platforms such as AWS, Azure, and GCP. - Champion emerging technologies like Agentic AI and advanced automation to drive innovation. - Build and manage strategic vendor and industry alliances to enhance partnerships. - Ensure delivery excellence by overseeing project execution with high quality, on-time, and on-budget outcomes. - Mentor and develop a high-performing team of data engineers, scientists, and AI specialists. Qualifications:
Minimum of 20 years of experience in data engineering, with a background in data warehousing and expertise in analytics/AI practice leadership. - Track record of designing and managing modern data platforms like Snowflake, Databricks, BigQuery, and Redshift. - Strong understanding of AI/ML concepts and their business applications. - Demonstrated proficiency in revenue recognition, profitability management, and practice P&L ownership. - Experience in establishing strategic partnerships and collaborating on go-to-market strategies. - Advanced technical skills in Spark, ETL/ELT processes, SQL/NoSQL databases, and data governance. - Excellent leadership abilities, effective communication skills, and adept stakeholder management. - Bachelors or Masters degree in Computer Science or Engineering; MBA qualification is preferred. This job description does not contain any additional details about the company.
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