Job Title Lead Data Engineer Location (s) Cochin Years of Experience 5-10yrs Job Description Lead Data Engineer What You’ll Do • Lead the design, development, and maintenance of scalable ETL/ELT pipelines and data products in multi-cloud, multi-region, distributed environments. • Define and apply appropriate data engineering patterns and architectures based on business and technical requirements. • Drive technical investigations and resolve complex data, operational, and production issues. • Design scalable, flexible, efficient, and supportable solutions using appropriate technologies and disciplined development practices. • Provide technical leadership, guidance, and mentorship to data engineering teams. • Collaborate with architects, engineering teams, and business stakeholders to deliver robust data solutions. Key Skills • Data Engineering & Architecture: Strong understanding of data engineering patterns and modern architectures such as Data Mesh, Data Fabric, Data Lake, and Data Warehouse. • Big Data & Cloud: Proficiency in Amazon EMR, AWS Glue, Data Lake, and technologies for processing large datasets. • Programming: Strong proficiency in Python, Java, or Scala, with solid OOP expertise. • Data Warehousing: Strong knowledge of data warehousing solutions, preferably Snowflake. • ETL/ELT & Orchestration: Hands-on experience with ETL/ELT pipelines and data orchestration tools. • Databases: Strong expertise in relational and NoSQL databases. • Data Modelling: Experience designing efficient OLAP and OLTP data models. • Streaming: Knowledge of streaming data technologies and architectures. • Version Control: Experience with Git and modern development practices. • Containers & Orchestration: Understanding of Docker and Kubernetes. • Data Security: Knowledge of encryption, access control, data privacy, and compliance. • Monitoring & Logging: Experience implementing monitoring, logging, alerting, and observability for data pipelines. Role & Responsibilities • Lead Data Engineer • What You’ll Do • Lead the design, development, and maintenance of scalable ETL/ELT pipelines and data products in multi-cloud, multi-region, distributed environments. • Define and apply appropriate data engineering patterns and architectures based on business and technical requirements. • Drive technical investigations and resolve complex data, operational, and production issues. • Design scalable, flexible, efficient, and supportable solutions using appropriate technologies and disciplined development practices. • Provide technical leadership, guidance, and mentorship to data engineering teams. • Collaborate with architects, engineering teams, and business stakeholders to deliver robust data solutions. • Key Skills • Data Engineering & Architecture: Strong understanding of data engineering patterns and modern architectures such as Data Mesh, Data Fabric, Data Lake, and Data Warehouse. • Big Data & Cloud: Proficiency in Amazon EMR, AWS Glue, Data Lake, and technologies for processing large datasets. • Programming: Strong proficiency in Python, Java, or Scala, with solid OOP expertise. • Data Warehousing: Strong knowledge of data warehousing solutions, preferably Snowflake. • ETL/ELT & Orchestration: Hands-on experience with ETL/ELT pipelines and data orchestration tools. • Databases: Strong expertise in relational and NoSQL databases. • Data Modelling: Experience designing efficient OLAP and OLTP data models. • Streaming: Knowledge of streaming data technologies and architectures. • Version Control: Experience with Git and modern development practices. • Containers & Orchestration: Understanding of Docker and Kubernetes. • Data Security: Knowledge of encryption, access control, data privacy, and compliance. • Monitoring & Logging: Experience implementing monitoring, logging, alerting, and observability for data pipelines. • Technical Qualifications Python + AWS EMR + AWS Glue + Snowflake + ETL/ELT + Data Engineering + Data Architecture + Big Data + SQL