Data Engineer | Mid to Senior  

Job Responsibilities

• Design, develop, and maintain ETL pipelines to ingest, transform, and load data from multiple sources.
• Build and optimize data pipelines for performance, reliability, and scalability.
• Work with cloud-based data lakehouse platforms such as Databricks, BigQuery, or similar technologies.
• Develop and maintain data processing workflows using Python.
• Write complex and optimized SQL queries to support analytics and reporting requirements.
• Design and manage data models to support data warehousing and business intelligence use cases.
• Process and manage structured and semi-structured data (e.g., JSON, CSV, logs).
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements.
• Ensure data quality, integrity, and consistency across data platforms.
• Troubleshoot and resolve data pipeline and performance issues.

Qualifications

• Bachelor’s degree in Information Technology, Computer Science, Engineering, or a related field.
• 3–4+ years of professional experience as a Data Engineer or in a similar role.
• Hands-on experience with ETL processes and data pipeline development.
• At least 1–2 years of hands-on experience with cloud-based data lakehouse platforms (e.g., Databricks, BigQuery).
• Strong programming skills in Python.
• Solid experience with SQL and relational databases.
• Good understanding of data warehousing concepts and data modeling.
• Ability to work with structured and semi-structured data.
• Strong problem-solving skills and attention to detail.