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.