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We are looking for a seasoned Principal Data Engineer with over 6 years of experience in data engineering, data modeling, and data architecture. The ideal candidate will have a deep understanding of the complexities involved in developing and maintaining data warehouses and data lakes. This role requires strong technical expertise, particularly in Python, and the ability to lead the design and implementation of data pipelines and ETL processes across diverse data sources.
Key Responsibilities:
- Lead the design, development, and optimization of data models and architectures for large-scale data warehouses and data lakes.
- Architect, build, and maintain sophisticated ETL pipelines that integrate data from various sources, including SQL, NoSQL, APIs, JSON, etc.
- Conduct in-depth data analysis, generate insights, and develop dashboards using cutting-edge BI tools.
- Drive the development of data pipelines and transformations using AWS Glue (Spark) and DBT, with a strong emphasis on Python for custom solutions.
- Oversee the management and optimization of databases and storage solutions such as PostgreSQL, MongoDB, Redis, S3, Redshift, and others.
- Ensure robust CI/CD pipeline integration and manage version control through git repositories.
- Utilize advanced Excel and Tableau skills for comprehensive data analysis and visualization.
Requirements
Minimum of 6 years of hands-on experience in data engineering, with a strong focus on data modeling, architecture, and the development of data warehouses/lakes.
Extensive experience in building and maintaining complex ETL pipelines from multiple data sources.
Expert-level Python coding skills, with a deep understanding of software development best practices.
Proven experience in developing data pipelines and transformations using AWS Glue (Spark) and DBT.
In-depth knowledge of databases and storage tools such as PostgreSQL, MongoDB, Redis, S3, Redshift, etc.
Strong experience with CI/CD pipelines and git repositories.
Advanced proficiency in Excel and Tableau for data analysis and dashboard creation.
Benefits
In addition to a market competitive compensation, we have a reward philosophy that expand beyond this.
- Fully remote with office optional. You decide when you would like to work from home and when from the office.
- Flexible timings. You decide your work scheduled.
- Market competitive compensation (in $$).
- Insane learning and growth
If you are a highly experienced Data Engineer with excellent Python coding skills and a passion for leading data architecture projects, we invite you to apply.
Pakistan
