| 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.
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| 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.
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| Technical Qualifications | Python + AWS EMR + AWS Glue + Snowflake + ETL/ELT + Data Engineering + Data Architecture + Big Data + SQL |
