Data Engineer

We are looking for a Data Engineer to join our data team and support the development of scalable, reliable, and high-quality data solutions across the organization. In this role, you will work closely with business stakeholders and technical teams to design and deliver pipelines, models, and architectures that enable advanced analytics, reporting, and operational decision-making.

Key Responsibilities

• Design, build, and maintain ETL/ELT pipelines to ingest, transform, and load data from various sources (operational systems, APIs, files, third-party platforms).
• Partner with business users and subject-matter experts across Finance, Operations, Procurement, Marketing, and other domains to understand business processes and translate them into robust data models.
• Implement and support Data Warehouse and Data Lakehouse architectures that ensure scalability, reliability, and efficient data access.
• Develop transformation logic using SQL, Python, and Spark, ensuring high performance and maintainability.
• Ensure data quality, consistency, and performance through monitoring, documentation, validation, and automation.
• Collaborate with BI, Data Science, and Data Governance teams to support analytics, reporting, machine learning, and data lifecycle initiatives.
• Contribute to the continuous improvement of data engineering practices, including CI/CD, DevOps/DataOps, coding standards, and automation.

Requirements

• 3+ years of experience as a Data Engineer or in a similar data-centric role.
• Hands-on experience with Databricks, Apache Spark, or comparable distributed data processing platforms.
• Strong proficiency in SQL and proven experience building scalable ETL/ELT pipelines.
• Solid programming skills in Python.
• Experience working with relational and non-relational databases.
• Strong analytical thinking, problem-solving abilities, and attention to detail.
• Excellent communication skills with the ability to collaborate with cross-functional and non-technical stakeholders.
• Good understanding of business processes such as Finance, Supply Chain, and Operations, and how data flows across these areas.