Senior Data Engineer

Role:

As a Senior Data Engineer, you will be instrumental in designing, building, and maintaining scalable data infrastructure using modern big data technologies. You will work closely with cross-functional teams including data scientists, analysts, and business stakeholders to ensure high-quality data availability and usability. This role requires strong technical expertise, a collaborative mindset, and a problem-solving attitude.

Responsibilities:

• Build and optimize data pipelines using Databricks, SQL, and Apache Spark.
• Design and implement scalable and reliable data processing systems.
• Develop and maintain robust ETL/ELT workflows for large-scale data sets.
• Manage and monitor data pipelines to ensure performance and efficiency.
• Ensure high standards of data quality, consistency, and integrity.
• Collaborate with team members to solve complex technical challenges, including pair programming.
• Participate in discussions to clarify requirements with business and technical stakeholders.
• Contribute to process and infrastructure improvements through automation and innovation.

Qualifications:

• Proven expertise in Databricks, SQL, and Apache Spark.
• Strong SQL skills for data querying, transformation, and optimization.
• Experience in data modeling and building ETL/ELT processes.
• Proficiency in Python for data scripting and workflow orchestration.
• Hands-on experience with AWS (especially S3, ECS) and cloud-native data engineering.
• Familiarity with Linux/Ubuntu operating systems.
• Experience with analytics engineering principles.
• Exposure to dbt (Data Build Tool) for transformation management.
• Understanding of machine learning-driven data workflows is a plus.