Data Engineer

Job Description: 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: 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: 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.