Data Engineer

Job Description

. We are seeking a Data Engineer to develop and maintain scalable data pipelines and support the organization's data and analytics platform.

. The role involves integrating multiple data sources and ensuring reliable, high-quality data processing for analytics, reporting, and machine learning initiatives.

. You will collaborate closely with analytics, product, and infrastructure teams to design and operationalize data pipelines while ensuring data governance, monitoring, and platform reliability.

Key Responsibilities

. Data Pipeline Development Develop and maintain ETL pipelines for centralized data storage and analytics platforms.

. Integrate data from various sources including databases, APIs, log files, streaming platforms, and external providers.

. Build and maintain data transformation processes to clean, normalize, and aggregate data.

. Apply advanced data processing techniques to handle complex and inconsistent datasets.

. Data Platform & Engineering Practices Contribute to data engineering frameworks, standards, and best practices for development and deployment.

. Implement data governance policies in alignment with organizational standards.

. Collaborate with analytics and product teams to design and operationalize data pipelines that support business insights.

. Work with infrastructure teams to enhance and maintain cloud-based data platforms.

. Explore and adopt new technologies leveraging platforms such as Azure, Databricks, or related cloud technologies.

. Monitoring & Reliability Monitor data pipelines and workflows to detect, troubleshoot, and resolve issues.

. Develop monitoring tools, alerts, and automated error-handling mechanisms to ensure system reliability.

Required Qualifications

. Open to candidates across a wide range of experience levels, including fresh graduates.

. Experience in designing data solutions and data modeling.

. Hands-on experience with data processing using Talend, PySpark, and SQL.

. Experience orchestrating data pipelines using Talend, Azure Data Factory (ADF), Airflow, or similar tools.

. Experience with batch and real-time data processing.

. Strong proficiency in SQL, including advanced features, with exposure to multiple data systems (e.g., SQL databases, Cloudera).

. Understanding of DevOps practices, including Git workflows, CI/CD pipelines, or MLOps.