Job SummaryWe are seeking a Lead Data Engineer with proven experience in designing, building, and delivering enterprise-scale data engineering solutions. The ideal candidate will have strong expertise in Hadoop, Apache Spark, SQL, ETL/ELT pipelines, and Splunk, along with experience leading technical initiatives and mentoring engineering teams.Key ResponsibilitiesDesign, develop, and optimize enterprise data engineering solutions using Hadoop, Apache Spark, SQL, and Python.Build and maintain scalable ETL/ELT pipelines for structured, semi-structured, and unstructured data.Develop data models and support the complete data ingestion, transformation, and processing lifecycle.Work with SQL, NoSQL, and big data technologies to deliver high-performance data solutions.Implement and maintain CI/CD pipelines and source control best practices.Collaborate with BI, Analytics, and cross-functional teams to deliver data-driven solutions.Ensure data quality, governance, resilience, scalability, and operational excellence.Lead technical initiatives, mentor junior engineers, and promote engineering best practices.Participate in Agile delivery using Scrum/Kanban methodologies.Troubleshoot complex data engineering challenges and drive continuous improvement.Required SkillsStrong hands-on experience with Apache Hadoop, Apache Spark, SQL, Python, and Splunk.Expertise in ETL/ELT pipeline development, data modeling, and big data processing.Experience with SQL/NoSQL databases, CI/CD pipelines, and source control.Strong analytical, problem-solving, stakeholder management, and communication skills.Experience leading technical teams and mentoring engineers.Understanding of engineering governance, risk management, and compliance.Mandatory Skills: Apache Spark, Hadoop Ecosystem, ETL Concepts, Splunk.

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