Join our dynamic team as a Data Engineering Lead, driving the creation and implementation of expansive cloud-based data solutions. This hands-on role requires deep expertise in data lakes, modern cloud platforms, and robust ETL/ELT pipelines. You will manage technical teams and client relationships, guiding projects from initial sales discussions through to successful delivery.

This is an opportunity to shape critical data infrastructure and mentor a talented engineering group.

Spearhead the design and deployment of scalable, cloud-native data engineering solutions and sophisticated data lakes.

Actively participate in pre-sales efforts, including client consultations, solution architecture, proposal development, and Proofs of Concept (PoCs).

Architect secure and scalable data storage solutions leveraging AWS, Azure, or GCP.

Construct and refine ETL/ELT pipelines using tools like Apache Spark, Databricks, AWS Glue, or Azure Data Factory.

Develop efficient data transformation and processing workflows with serverless technologies such as AWS Lambda or Azure Functions.

Implement comprehensive data governance, security protocols, and data quality frameworks.

Collaborate closely with data scientists, BI specialists, and business stakeholders to ensure reliable analytics capabilities.

Lead and mentor a team of data engineers throughout the project lifecycle, fostering growth and best practices.

Optimize cloud infrastructure, storage, and processing expenditures while upholding high performance and reliability standards.

Ensure the seamless delivery of projects, meeting both client expectations and strategic business objectives.

A minimum of 5 years of practical experience in Data Engineering and cloud-based data solutions is essential.

Demonstrated strong expertise in at least one major cloud platform: AWS, Azure, or Google Cloud Platform.

Proven experience in designing and implementing robust Data Lakes.

Hands-on proficiency with ETL/ELT tools such as Apache Spark, Databricks, AWS Glue, or Azure Data Factory.

Familiarity with serverless computing environments, including AWS Lambda, Azure Functions, or Google Cloud Functions.

A solid grasp of data governance, data quality management, security principles, and compliance requirements.

Experience with containerization technologies like Docker and orchestration tools like Kubernetes.

Strong programming skills in SQL, Python, Scala, or Java are required.

Experience working with cloud data warehouses like Amazon Redshift, Google BigQuery, or Azure Synapse.

Substantial leadership experience managing technical teams and delivering projects end-to-end, from pre-sales engagement to full implementation.

Excellent communication and stakeholder management abilities are critical for success in this role.