Data Engineering Practice Head

As the Data Engineering Practice Head at Everest DX, you will play a crucial role in driving the data engineering strategy aligned with business goals and digital transformation initiatives. Your responsibilities will include setting the vision, strategy, and execution roadmap for enterprise-wide data engineering initiatives, overseeing the design, development, and deployment of scalable data platforms and pipelines, and ensuring high-quality data infrastructure to support analytics, machine learning, and business intelligence capabilities. **Key Responsibilities:** - Define and lead the overall data engineering strategy aligned with business goals and digital transformation initiatives. - Build, mentor, and manage high-performing data engineering teams across geographies. - Drive the design and implementation of robust, scalable data architectures including data lakes, warehouses, and real-time data platforms. - Lead the development and operationalization of advanced ETL/ELT frameworks, data pipelines, and API-based data services. - Collaborate with stakeholders across data science, analytics, and application teams to ensure data availability, quality, and governance. - Establish best practices, standards, and frameworks for data engineering workflows, CI/CD, data modeling, and pipeline monitoring. - Evaluate and adopt new tools, technologies, and methodologies to enhance performance and productivity. - Partner with compliance and security teams to ensure data privacy, protection, and regulatory adherence. **Required Skills and Qualifications:** - 15+ years of experience in data engineering, data architecture, or related fields, with at least 5 years in a leadership role. - Proven expertise in modern data platforms and tools such as Azure Data Services, AWS, GCP, Databricks, Snowflake, Kafka, Spark, Airflow. - Deep understanding of data architecture principles, data modeling (relational & NoSQL), and pipeline orchestration. - Hands-on experience with languages such as Python, SQL, Scala, or Java. - Strong knowledge of cloud-native architectures and DevOps for data systems. - Exceptional leadership, communication, and stakeholder management skills. - Bachelors or Masters degree in Computer Science, Engineering, or a related field; advanced certifications in data technologies are a plus. **Preferred Qualifications:** - Experience in leading data transformation programs in large enterprises or consulting environments. - Familiarity with data governance frameworks and metadata management. - Exposure to AI/ML use cases and MLOps platforms. Join Everest DX for continuous learning opportunities, a dynamic and collaborative culture, an agile work environment, and exposure to innovative solutions in digital transformation. Visit [Everest DX](http://www.everestdx.com) to know more about the company.,