Junior Data Engineer
3 days ago
The Junior Data Engineer will be responsible for creating, maintaining, and modifying data pipelines for the reporting and system's needs.
DUTIES & RESPONSIBILITIES
- Design, build, and orchestrate scalable data workflows and architecture aligned with business goals. Develop and maintain robust batch and real-time data pipelines using modern tools and platforms.
- Manage structured and unstructured databases with a focus on performance, availability, and optimisation
- Ensure high standards of data quality, consistency, and accessibility across integrated systems
- Collaborate with cross-functional teams to gather requirements and translate them into data solutions
- Implement data governance standards covering security, privacy, and compliance
- Proactively monitor and troubleshoot system performance, ensuring uptime and reliability of pipelines
- Transform raw data into clean, well-documented, and report-ready datasets
- Maintain clear documentation of data processes, workflows, and architecture for knowledge sharing
- Other duties as assigned by the manager
KNOWLEDGE & EXPERIENCE
Education:
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field
Experience:
- 3+ years of experience working with data-driven solutions, with a focus on transforming healthcare or operational datasets into actionable insights to support process improvement and analytics initiatives.
- 2+ years of experience collaborating with stakeholders to design, build, and deploy scalable data engineering deliverables, including data pipelines, ETL workflows, and integrated data models tailored for analytical needs
- 2+ years of experience creating and maintaining self-service data infrastructure, such as datasets, dashboards, and backend integrations that empower end-users to explore metrics and monitor KPIs through BI tools
Credentials:
- Industry certifications in data engineering or cloud platforms/frameworks.
Knowledge and Skills:
- Data architecture design and data modeling (relational & dimensional), Development of batch and real-time data pipelines using ETL/ELT tools
- Strong proficiency in SQL, Python, and optionally Scala/Java
- Hands-on experience with cloud platforms: AWS, Azure, GCP
- Advanced database management with SQL Server, PostgreSQL, MongoDB, etc.
- Experience with big data technologies like Spark, Hadoop, and Kafka
- Data quality assurance, profiling, cleansing, and governance practices
- Use of orchestration and workflow tools such as Apache Airflow, DBT, and Talend
- Expertise in Microsoft Excel (pivot tables, macros, Google scripts)
- Familiar with documentation and design tools: Microsoft Word, PowerPoint, Visio, G Suite
- Skilled in handling and optimizing large-scale datasets and infrastructure
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