Data Engineer

Job Title

Location (s)

Cochin

Years of Experience

5-10yrs

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