Senior Data Engineering Lead

Job description:

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.

Skills

AWS, Azure, Data Engineering, Data Lake, Databricks, ELT, ETL, GCP, Google Cloud Platform, Spark