Lead Senior Associate | Data Engineering

Job Title: Data Engineering Lead Experience: 8-10 Years 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.