Software Engineer, Data

Devsinc

full-time

Posted on: 9/22/2025

Origin: • 🇵🇰 Pakistan

✨ AI Apply

Junior

ApacheETLHadoopMongoDBMySQLPostgresPythonSparkSQLTableau

About the role

Design, develop, and maintain scalable data pipelines to ensure high-quality data accessibility for analytics and modeling.
Implement and optimize ETL processes, focusing on data transformation, integration, and cleansing.
Collaborate with cross-functional teams to understand data requirements and deliver effective data models that support business analytics.
Apply statistical analysis and machine learning techniques to solve complex data challenges and generate actionable insights.
Monitor and troubleshoot data systems, ensuring data integrity and performance optimization across data workflows.
Stay current with industry trends, technologies, and best practices in data engineering and data science.
Contribute to the development of dashboards and reporting tools to visualize data and support decision-making processes.
Document data processes and architectures to facilitate knowledge sharing and promote compliance with data governance standards.

Bachelor’s degree in Data Science, Computer Science, Engineering, Mathematics, or a related field.
1-3 years of experience in data engineering, data science, or related roles.
Proficiency in SQL and experience with database management (e.g., PostgreSQL, MySQL, MongoDB).
Experience with data engineering tools and frameworks such as Apache Spark, Hadoop, or similar technologies.
Solid understanding of machine learning algorithms and experience implementing predictive analytics models.
Familiarity with programming languages such as Python or R for data processing and analysis.
Knowledge of data visualization tools (e.g., Tableau, Power BI) is a plus.
Excellent problem-solving abilities and analytical skills, with a keen attention to detail.
Strong communication skills, capable of presenting complex data concepts to technical and non-technical stakeholders.
A collaborative mindset, with the ability to work effectively in a team environment.
Commitment to continuous learning and professional development in data science and engineering.