Data Engineer at IBS Software – India | Jobyssey

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

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