Job Title: Data Engineering Lead About the Role We are looking for a hands-on Data Engineering Lead to lead the design, implementation, and delivery of large-scale cloud-based data engineering solutions. The ideal candidate will have strong expertise in data lakes, cloud platforms, ETL/ELT pipelines, and modern data architecture while managing technical teams and client engagements from pre-sales through project delivery. Key Responsibilities • Lead the design and implementation of scalable cloud-based data engineering solutions and data lakes. • Drive pre-sales activities, including client discussions, solution design, technical proposals, and Proof of Concepts (PoCs). • Design secure and scalable data storage architectures using AWS, Azure, or GCP. • Build and optimize ETL/ELT pipelines using Apache Spark, Databricks, AWS Glue, Azure Data Factory, or similar technologies. • Develop efficient data transformation and processing workflows using serverless technologies such as AWS Lambda, Azure Functions, or Google Cloud Functions. • Implement data governance, security, and data quality frameworks. • Collaborate with data scientists, BI teams, and business stakeholders to enable reliable analytics. • Lead and mentor a team of data engineers throughout the project lifecycle. • Optimize cloud infrastructure, storage, and processing costs while maintaining performance and reliability. • Ensure successful project delivery aligned with client and business objectives. Required Skills • 5+ years of hands-on experience in Data Engineering and cloud-based data solutions. • Strong expertise in AWS, Azure, or Google Cloud Platform. • Experience designing and implementing Data Lakes. • Hands-on experience with Apache Spark, Databricks, AWS Glue, Azure Data Factory, or similar ETL tools. • Experience with serverless computing (AWS Lambda, Azure Functions, Google Cloud Functions). • Strong understanding of data governance, data quality, security, and compliance. • Experience with Docker and Kubernetes. • Strong programming skills in SQL, Python, Scala, or Java. • Experience with cloud data warehouses such as Amazon Redshift, Google BigQuery, or Azure Synapse. • Proven leadership experience managing technical teams and delivering projects from pre-sales through implementation. • Excellent communication and stakeholder management skills. Preferred Qualifications • Experience with AWS Lake Formation, Azure Purview, or Google Data Catalog. • Cloud certifications (AWS, Azure, or GCP). • Experience with CI/CD pipelines and DevOps practices.