Data Engineer

Responsibilities

• ● We are looking for passionate and curious Data Engineers who enjoy solving complex data challenges and building modern data platforms. If you love working with large-scale data, designing efficient pipelines, exploring cloud technologies, and continuously learning new tools, this role is for you. Hands-on experience or strong interest in Databricks, Snowflake, Spark, SQL, Python, and cloud-based data engineering is highly desirable. Whether through academic projects, certifications, hackathons, or personal initiatives, we value candidates who demonstrate a genuine passion for data and a drive to build innovative data solutions.
• ● 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.