Description

You will build and maintain scalable ELT pipelines and data transformation models within a structured CI/CD environment.

This role is remote.

Responsibilities

• Develop Python and SQL scripts for data profiling, including column statistics, outlier checks, and quality validations.
• Create and maintain source-to-target mappings in GitLab, documenting business rules, lineage, and edge cases.
• Build ingestion pipelines using Mage and develop staging, cleansing, and mart-level models using dbt.
• Implement data quality tests and monitor SLAs to enforce merge blocking on pipeline failures.
• Maintain technical documentation, including runbooks, S2T documents, and pipeline diagrams, within 3 business days of changes.

Required Skills

• 5+ years of experience in Data Engineering.
• Advanced SQL expertise, including window functions and performance tuning.
• Proficiency in Python for data processing using Pandas or PySpark.
• Hands-on experience with Mage orchestration and dbt modeling.
• Experience with GitLab workflows, including branching, merge requests, and CI/CD deployments.
• Strong understanding of data modeling, lineage tracking, and data quality frameworks.
• Ability to work with PySpark and Databricks.

Preferred Skills

• Experience with Snowflake, BigQuery, Redshift, or Azure Synapse.
• Exposure to Airflow and BI tools such as Power BI, Tableau, or Looker.

Key Skills

Education

Any Graduate