Seeking a hands-on Data Engineering Lead to spearhead the design, implementation, and delivery of extensive cloud-based data engineering solutions. This role demands significant expertise in data lakes, cloud platforms, ETL/ELT pipelines, and contemporary data architectures.

Key responsibilities include managing technical teams and guiding client engagements from initial pre-sales discussions through to successful project completion. This leadership position is pivotal in shaping our data engineering capabilities.

Lead the development and deployment of robust, scalable cloud data engineering solutions and data lakes. Drive pre-sales initiatives, including client consultations, solution architecture, proposal creation, and Proof of Concepts.

Design secure and scalable data storage solutions utilizing AWS, Azure, or GCP. Build and optimize ETL/ELT pipelines using tools like Apache Spark, Databricks, AWS Glue, or Azure Data Factory. Develop efficient data transformation workflows with serverless technologies.

Implement comprehensive data governance, security protocols, and data quality frameworks. Foster collaboration with data scientists, BI specialists, and business stakeholders to ensure reliable analytics. Mentor and guide a team of data engineers throughout project lifecycles.

Optimize cloud infrastructure costs, storage, and processing efficiency while upholding performance and reliability standards. Ensure the successful delivery of projects, meeting both client expectations and business objectives.

A minimum of 8 years of hands-on experience in Data Engineering and cloud data solutions is required. Extensive proficiency in AWS, Azure, or Google Cloud Platform is essential, along with proven experience in designing and implementing Data Lakes.

Demonstrated experience with Apache Spark, Databricks, AWS Glue, Azure Data Factory, or equivalent ETL tools is crucial. Familiarity with serverless computing (AWS Lambda, Azure Functions, Google Cloud Functions) and a strong grasp of data governance, quality, security, and compliance are necessary.

Experience with Docker and Kubernetes is required. Strong programming skills in SQL, Python, Scala, or Java are a must. Proficiency with cloud data warehouses such as Amazon Redshift, Google BigQuery, or Azure Synapse is expected. Proven leadership experience in managing technical teams and delivering projects from pre-sales to implementation, coupled with excellent communication and stakeholder management skills, is vital for success in this role.