Data Engineer

Naviq; India; On-site; INR 800,000 - 1,600,000; Full time

Job summary

Naviq is seeking a data engineering professional to design and build data processing ETL pipelines and data products across multi-cloud environments.

You will drive data investigations and resolve technical, procedural, and operational issues, delivering scalable and efficient solutions using appropriate technologies.

Qualifications

• Knowledge of data engineering patterns to determine what to use and when.
• Understanding of data architecture and frameworks like Data mesh, data fabric.
• Proficiency in big data technologies such as data lake, EMR, Glue.
• Proficiency in programming languages such as Python, Java, or Scala with OOP.
• Strong knowledge of data warehousing, preferably Snowflake.
• Familiarity with orchestration tools for ETL/ELT.
• Expertise in relational and NoSQL databases.
• Skill in designing efficient data models for OLAP/OLTP.
• Knowledge of streaming data technologies.
• Experience with Git.
• Understanding of Docker and Kubernetes.
• Knowledge of data encryption, access control, and privacy regulations.
• Proficiency in monitoring and logging data pipelines.

Responsibilities

• Design, build and maintain data processing ETL pipelines & data products in a multi-cloud, multi-region, distributed processing context choosing the right technologies.
• Drive data investigations to deliver a resolution of technical, procedural, and operational issues.
• Solve complex business problems by utilizing disciplined development methodology, producing scalable, flexible, efficient and supportable solutions using appropriate technologies.

Skills

Data engineering patterns

Data architecture

Big Data Technologies

Programming Languages (Python/Java/SCa

Data Warehousing

Data Modelling

Streaming Data

Data Security

Monitoring and Logging

Tools

Git

Docker

Kubernetes

ETL/ELT Tools

Relational Databases

NoSQL Databases

Job description

What you’ll do

• Design, build and maintain data processing ETL pipelines & data products in a multi-cloud, multi-region, distributed processing context choosing the right technologies.
• Drive data investigations to deliver a resolution of technical, procedural, and operational issues.
• Solve complex business problems by utilizing disciplined development methodology, producing scalable, flexible, efficient and supportable solutions using appropriate technologies.

Skills

• Data engineering patterns: Sound knowledge of the different data engineering patterns to determine what to use and when
• Data architecture: Understanding of data architecture and frameworks like Data mesh, data fabric etc.
• Big Data Technologies: Proficiency in big data technologies such as data lake, EMR, Glue for analysing large datasets.
• Programming Languages: Proficiency in programming languages commonly used in data engineering, such as Python, Java, or Scala. with OOP expertise
• Data Warehousing: Strong knowledge of data warehousing solutions preferably Amazon Snowflake.
• ETL/ELT Tools: Familiarity with orchestration tools
• Database Systems: Expertise in both relational and NoSQL databases.
• Data Modelling: Skill in designing efficient data models, both for OLAP and OLTP systems.
• Streaming Data: Knowledge of streaming data technologies.
• Version Control: Experience with version control systems : Git.
• Containerization and Orchestration: Understanding of containerization technologies (Docker) and container orchestration platforms (Kubernetes).
• Data Security: Knowledge of data encryption, access control, and compliance with data privacy regulations.
• Monitoring and Logging: Proficiency in setting up monitoring and logging solutions for data pipelines using different tools