Seeking a hands-on Data Engineering Lead to spearhead the design, implementation, and delivery of extensive cloud-based data engineering solutions. This role requires deep expertise in data lakes, cloud platforms, ETL/ELT pipelines, and modern data architectures. The ideal candidate will also excel in managing technical teams and client interactions throughout the project lifecycle, from initial pre-sales discussions to successful project completion.

This is a pivotal role focused on building robust and scalable data infrastructures. You will be instrumental in shaping our data strategy and ensuring the successful execution of complex data projects.

Lead the architecture and deployment of scalable cloud data engineering solutions and data lakes. Drive pre-sales initiatives, including client consultations, solution conceptualization, technical proposal creation, and Proof of Concepts (PoCs). Architect secure and scalable data storage frameworks on AWS, Azure, or GCP. Develop and optimize ETL/ELT pipelines utilizing technologies like Apache Spark, Databricks, AWS Glue, or Azure Data Factory. Implement efficient data transformation and processing workflows using serverless computing services such as AWS Lambda or Azure Functions. Establish and maintain robust data governance, security, and data quality frameworks. Partner with data scientists, BI teams, and business stakeholders to facilitate reliable data analytics. Guide and mentor a team of data engineers, overseeing their contributions throughout project timelines. Optimize cloud infrastructure, storage, and processing expenditures while upholding performance and reliability standards. Ensure the successful delivery of projects, meeting both client expectations and business objectives.

A minimum of 5 years of practical experience in Data Engineering and cloud-based data solutions is essential. Demonstrated expertise in AWS, Azure, or Google Cloud Platform. Proven experience in designing and implementing Data Lakes. Hands-on proficiency with Apache Spark, Databricks, AWS Glue, Azure Data Factory, or comparable ETL tools. Experience with serverless computing technologies like AWS Lambda, Azure Functions, or Google Cloud Functions. A strong grasp of data governance, data quality, security, and compliance principles. Familiarity with Docker and Kubernetes. Advanced programming skills in SQL, Python, Scala, or Java. Experience with cloud data warehouses such as Amazon Redshift, Google BigQuery, or Azure Synapse. Substantial leadership experience in managing technical teams and delivering projects from pre-sales through to implementation. Exceptional communication and stakeholder management capabilities.