Data Enginer

Role Description
We are looking for a skilled and detail-oriented Data Engineer to design, build, and maintain reliable data infrastructure, pipelines, and processing solutions. You will work closely with data analysts, data scientists, software engineers, and business stakeholders to ensure data is accurate, accessible, scalable, and secure.
You will develop and optimize ETL/ELT pipelines, integrate data from multiple sources, and build efficient workflows for data ingestion, transformation, storage, and delivery. You will also contribute to data warehouse and data lake solutions, data modeling, and the development of reusable data processing frameworks.
The role involves monitoring pipeline performance and data quality, troubleshooting data issues, improving system reliability, and implementing appropriate validation and monitoring processes. You will work with stakeholders to understand data requirements and translate them into scalable and maintainable technical solutions.
You will also contribute to data architecture, documentation, governance, security, and access-control practices. You will identify opportunities to automate manual processes, improve data availability and processing efficiency, and support the continuous improvement of the organization's data platform.
Qualifications
Bachelor’s degree or above in Computer Science, Data Engineering, Information Technology, Software Engineering, Mathematics, Engineering, or a related field.
Strong understanding of data structures, databases, data modeling, ETL/ELT processes, and data engineering principles.
Strong proficiency in SQL and familiarity with relational databases, data warehouses, and data lakes.
Proficiency in Python, Java, Scala, or a similar programming language.
Familiarity with data pipeline and workflow orchestration tools such as Apache Airflow, Dagster, or equivalent platforms.
Understanding of distributed data processing technologies such as Apache Spark, Kafka, or similar technologies is a plus.
Familiarity with cloud platforms and data services such as AWS, Microsoft Azure, or Google Cloud.
Good understanding of data quality, validation, governance, security, and access-control principles.
Strong analytical and problem-solving skills with the ability to troubleshoot complex data and pipeline issues.
Familiarity with Git, CI/CD, testing practices, and software development workflows.
Ability to design scalable, reliable, and maintainable data solutions based on business and technical requirements.
Strong communication and collaboration skills with the ability to work effectively across technical and business teams.
Strong attention to detail and commitment to data accuracy, reliability, and documentation.
Proactive and continuous-learning mindset with an interest in emerging data technologies, cloud platforms, and modern data architecture.

Work arrangement
No