Etl Developer

Role Overview

We are seeking a talented ETL Engineer to design, implement, and maintain end-to-end data ingestion and transformation pipelines in Google Cloud Platform (GCP). This role will collaborate closely with data architects, analysts, and BI developers to ensure high-quality, performant data delivery into BigQuery and downstream Power BI reporting layers.

Key Responsibilities

• Data Ingestion & Landing
  
• Architect and implement landing zones in Cloud Storage for raw data.
  
• Manage buckets/objects and handle diverse file formats (Parquet, Avro, CSV, JSON, ORC).
  
• ETL Pipeline Development
  
• Build and orchestrate extraction, transformation, and loading workflows using Cloud Data Fusion.
  
• Leverage Data Fusion Wrangler for data cleansing, filtering, imputation, normalization, type conversion, splitting, joining, sorting, union, pivot/unpivot, and format adjustments.
  
• Data Modeling
  
• Design and maintain fact and dimension tables using Star and Snowflake schemas.
  
• Collaborate on semantic layer definitions to support downstream reporting.
  
• Load & Orchestration
  
• Load curated datasets into BigQuery across different zones (raw, staging, curated).
  
• Develop SQL-based orchestration and transformation within BigQuery (scheduled queries, scripting).
  
• Performance & Quality
  
• Optimize ETL jobs for throughput, cost, and reliability.
  
• Implement monitoring, error handling, and data quality checks.
  
• Collaboration & Documentation
  
• Work with data analysts and BI developers to understand requirements and ensure data readiness for Power BI.
  
• Maintain clear documentation of pipeline designs, data lineage, and operational runbooks.
  

Required Skills & Experience

• Bachelors degree in Computer Science, Engineering, or related field.
  
• 3+ years of hands-on experience building ETL pipelines in GCP.
  
• Proficiency with Cloud Data Fusion, including Wrangler transformations.
  
• Strong command of SQL, including performance tuning in BigQuery.
  
• Experience managing Cloud Storage buckets and handling Parquet, Avro, CSV, JSON, and ORC formats.
  
• Solid understanding of dimensional modeling: fact vs. dimension tables, Star and Snowflake schemas.
  
• Familiarity with BigQuery data zones (raw, staging, curated) and dataset organization.
  
• Experience with scheduling and orchestration tools (Cloud Composer, Airflow, or BigQuery scheduled queries).
  
• Excellent problem-solving skills and attention to detail.
  

Preferred (Good to Have)

• Exposure to Power BI data modeling and DAX.
  
• Experience with other GCP services (Dataflow, Dataproc).
  
• Familiarity with Git, CI/CD pipelines, and infrastructure as code (Terraform).
  
• Knowledge of Python for custom transformations or orchestration scripts.
  
• Understanding of data governance best practices and metadata management.