Data Analytics Professional

About the role

We are seeking a highly skilled Data Analytics Professional to develop and support modern data platforms that enable business intelligence, advanced analytics and operational insights. The successful candidate will have strong expertise in building scalable data pipelines, managing streaming and batch workloads and ensuring data quality across complex enterprise ecosystems. This role requires hands-on experience with cloud-native data technologies across both Google Cloud Platform (GCP) and AWS, with a specific focus on Kafka-based ingestion, analytics engineering and data platform reliability.

What you’ll be doing

• Design, build, and maintain scalable batch and real-time data pipelines using Apache Kafka and cloud-native data services.
• Develop robust ETL/ELT solutions using Python and SQL to ingest, transform, validate, and curate large-scale datasets.
• Implement and manage orchestration workflows using Apache Airflow and GCP Composer.
• Develop serverless data processing capabilities using GCP Cloud Functions, AWS Lambda, and AWS Glue.
• Design and implement data quality frameworks, including validation rules, monitoring, reconciliation processes, and automated remediation workflows.
• Build and optimise analytical data models and datasets within GCP Big Query and AWS analytics platforms.
• Manage data storage and querying solutions using Amazon S3 and Amazon Athena.
• Monitor pipeline performance, troubleshoot production issues, and implement improvements to ensure reliability, scalability, and operational efficiency.
• Collaborate with data engineers, analysts, architects, and business stakeholders to deliver trusted and actionable data products.
• Ensure security, governance, metadata management, and compliance standards are embedded throughout the data lifecycle.
• Contribute to CI/CD, automation, documentation, and best practices within the data engineering function.

Essential Skills / Experience

• Strong experience in data analytics and data product lifecycle management.  
• Hands-on expertise with Apache Kafka and event-driven data architectures.
• Advanced programming skills in Python and strong SQL development experience.
• Proven experience implementing data quality controls, data validation frameworks, and data governance practices.
• Experience working with: GCP Big Query, Apache Airflow / GCP Composer, GCP Cloud Functions, AWS Lambda, AWS Glue, Amazon S3, Amazon Athena
• Knowledge of data modelling, schema management, partitioning, and query optimisation techniques.
• Experience with source control, CI/CD pipelines, testing, and deployment automation.
• Strong troubleshooting, analytical, and problem-solving capabilities.
• Results-oriented with a strong focus on quality and operational excellence.
• Excellent communication and stakeholder management skills.
• Able to work independently while collaborating effectively within cross-functional teams.
• Passionate about continuous improvement, automation, and innovation in data platforms.