Data Engineering, DataBricks
Data Engineer Tech Lead Experience 10–13 Years Key Responsibilities We are looking for a highly skilled Data Engineer – Tech Lead with strong expertise in AWS, Databricks, PySpark, ETL, and Delta Live Tables (DLT). The candidate should be capable of understanding business requirements, interacting directly with clients, proposing scalable data architectures, and driving solution discussions to build client confidence. Design and implement scalable data engineering solutions on AWS and Databricks. Develop and optimize ETL/ELT pipelines using PySpark and DLT. Lead architecture discussions and recommend best-fit data solutions.Collaborate with business stakeholders and clients to understand requirements and translate them into technical solutions. Drive technical conversations, solution presentations, and client communication.Mentor engineering teams and ensure best practices in data engineering and cloud architecture.Ensure performance, scalability, security, and reliability of data platforms. Strong hands-on experience in AWS, Databricks, PySpark, ETL, and Delta Live Tables (DLT). Good understanding of modern data lakehouse architecture. Experience in data modeling, orchestration, and pipeline optimization. Strong communication and stakeholder management skills. Ability to lead client discussions and provide solution-oriented approaches. Experience in Agile delivery and team leadership. Exposure to CI/CD, DevOps, and data governance frameworks. Relevant AWS or Databricks certifications are a plus.
Data Engineer Tech Lead Experience 10–13 Years Key Responsibilities We are looking for a highly skilled Data Engineer – Tech Lead with strong expertise in AWS, Databricks, PySpark, ETL, and Delta Live Tables (DLT). The candidate should be capable of understanding business requirements, interacting directly with clients, proposing scalable data architectures, and driving solution discussions to build client confidence. Design and implement scalable data engineering solutions on AWS and Databricks. Develop and optimize ETL/ELT pipelines using PySpark and DLT. Lead architecture discussions and recommend best-fit data solutions.Collaborate with business stakeholders and clients to understand requirements and translate them into technical solutions. Drive technical conversations, solution presentations, and client communication.Mentor engineering teams and ensure best practices in data engineering and cloud architecture.Ensure performance, scalability, security, and reliability of data platforms. Strong hands-on experience in AWS, Databricks, PySpark, ETL, and Delta Live Tables (DLT). Good understanding of modern data lakehouse architecture. Experience in data modeling, orchestration, and pipeline optimization. Strong communication and stakeholder management skills. Ability to lead client discussions and provide solution-oriented approaches. Experience in Agile delivery and team leadership. Exposure to CI/CD, DevOps, and data governance frameworks. Relevant AWS or Databricks certifications are a plus.