Data Engineer

Role Overview:

As a Databricks & Snowflake Data Engineer, you will work closely with experienced data engineers, architects, and analytics teams to design, build, and optimize modern data platforms. You will be involved in the end-to-end data engineering lifecycle—from data ingestion and transformation to pipeline orchestration, data modeling, and performance optimization.

This role offers a hands-on learning environment where you'll work on real-world business challenges, gain exposure to cloud-based data platforms, and develop expertise in modern data engineering technologies including Databricks, Snowflake, Spark, Python, SQL, and cloud ecosystems.

Responsibilities

• Work with senior data engineers and architects to build, optimize, and maintain scalable data pipelines and workflows.
• Develop ETL/ELT processes using Databricks, Spark, Python, and SQL.
• Design and implement data ingestion frameworks for structured and unstructured data sources.
• Build and maintain data models, data marts, and analytical datasets in Snowflake.
• Monitor, troubleshoot, and improve data pipeline performance, reliability, and scalability.
• Collaborate with business stakeholders, analysts, and data scientists to understand data requirements and deliver solutions.
• Participate in architecture discussions, proof-of-concepts, and process improvement initiatives.
• Document data flows, technical designs, and implementation details to support operational excellence and knowledge sharing.
• Ensure adherence to data quality, security, and governance standards across data platforms.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical field.
• Strong foundation in SQL and database concepts.
• Good programming skills in Python or a similar language.
• Understanding of data warehousing concepts, ETL/ELT processes, and data modeling.
• Familiarity with Databricks, Apache Spark, Snowflake, or cloud data platforms through academic projects, internships, certifications, hackathons, or personal projects.
• Basic knowledge of cloud platforms such as Azure, AWS, or GCP is a plus.
• Strong analytical and problem-solving skills with a passion for learning modern data engineering technologies.
• Excellent communication and collaboration skills.