Data Engineer (Cloud & Analytics Platform)

The incumbent will design build and maintain scalable data solutions that support analytics machine learning and business insights. Responsibilities include developing robust data pipelines cloud-based data platforms analytics solutions and supporting AI/ML initiatives while ensuring data quality governance and operational excellence.

Responsibilities

• Design develop and maintain ETL/ELT pipelines across cloud and on-premise environments integrating internal and external data sources including compliant ingestion of public data where required.
• Build optimize and maintain scalable data models (e.g. star and snowflake schemas) to support analytics reporting and business intelligence requirements.
• Ensure data quality integrity and availability through validation cleansing transformation processes and implementation of monitoring controls.
• Implement and manage cloud-based data solutions on Microsoft Azure including Azure Data Factory Data Lake Storage Azure SQL and related services.
• Support infrastructure configuration and administration including compute storage networking identity management and security controls to ensure reliable and scalable platform operations.
• Implement CI/CD pipelines automate deployments and establish monitoring logging and alerting capabilities to maintain performance reliability and SLA adherence.
• Support the development and optimization of interactive dashboards and reports using Power BI ensuring seamless integration between data pipelines and reporting layers.
• Collaborate with business stakeholders to understand requirements and translate them into effective data solutions and visualizations.
• Collaborate with Data Scientists to deploy support and monitor machine learning models in production environments and integrate AI/ML capabilities into data pipelines and applications.
• Ensure adherence to data governance security compliance access control and data lineage requirements while following software engineering best practices such as version control code reviews and modular design.
• Contribute to continuous improvement of data platform standards operational performance scalability and cost optimization initiatives.

Requirements

• Possess a bachelors degree in Computer Science Computer Engineering or a related field.
• 23 years of experience in data engineering software engineering or related roles with exposure to data platforms cloud technologies and analytics solutions.
• Strong analytical thinking problem-solving and troubleshooting abilities.
• Good communication and collaboration skills with the ability to work effectively across technical and business teams.
• Self-motivated detail-oriented and able to manage multiple priorities in a dynamic environment.
• Possess initiative and willingness to learn new technologies tools and methodologies.

Technical Skills Required

• Experience with data warehousing concepts data modeling database optimization techniques and ETL/ELT development using Python or ETL tools (e.g. SSIS Informatica).
• Proficiency in relational database technologies such as Microsoft SQL Server and Oracle and familiarity with big data technologies such as Spark and Databricks.
• Proficiency in Python for data processing data engineering tasks and basic API development.
• Hands-on experience with Microsoft Azure services including Azure Data Factory Data Lake Storage and Azure SQL.
• Familiarity with CI/CD pipelines DevOps practices and automation tools such as Azure DevOps.
• Familiarity with streaming or real-time data processing concepts and exposure to monitoring performance tuning and optimization of data systems.
• Experience with Power BI including DAX and Power Query for dashboard development and reporting.
• Basic understanding of machine learning workflows and tools including Scikit-learn and Azure Machine Learning.

Only shortlisted candidates will be notified.