As a Data Engineer, you will be responsible for designing, developing, and maintaining data solutions for data generation, collection, and processing. Your day-to-day activities will include creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across systems.
You are expected to be a subject matter expert, collaborate and manage the team to perform effectively. You will be responsible for team decisions, engage with multiple teams, and contribute to key decisions while providing solutions to problems for your immediate team and across multiple teams.
Job Responsibilities
Develop innovative data solutions that enhance data accessibility and usability.
Collaborate with cross-functional teams to identify data needs and implement effective solutions.
Monitor and optimize data pipelines for performance and reliability.
Conduct regular data quality assessments and implement improvements as necessary.
Stay updated with industry trends and best practices in data engineering to continuously improve processes.
Query, clean, and transform datasets using SQL and Python on Databricks/Pyspark.
Ensure data quality and consistency across systems in accordance with government Instruction Manual (IM8) standards.
Build, enhance, and maintain dashboards for data monitoring, performance reporting, and user behaviour analytics.
Partner with business stakeholders to understand data requirements and translate them into impactful visual insights.
Develop clear and comprehensive user guides for dashboards, charts, and data workflows in Databricks
Maintain technical documentation (e.g., on Confluence) for analytics processes, standards, and best practices.
Job Qualification
Degree in Computer Science, Information Systems, Data Engineering, or a related field
With 3 or more years of hands-on experience in data engineering, data pipelines, and ETL processes.
Proficiency in SQL and Python for data processing and automation.
Hands-on experience in dashboard tools such as Tableau, Power BI, or equivalent visualisation tools.
Experience with Databricks or similar big data/analytics platforms.
Ability to produce high-quality technical documentation.
Experience in system testing, SIT/UAT, or quality assurance processes.
Knowledge of Spark for distributed data processing.
Understanding of Git or other version control systems.
Holds a Databricks certification.
Excellent analytical mindset and problem-solving abilities.
Good communication skills, especially in explaining technical concepts to non-technical users.
Ability to work independently as well as collaboratively in cross-functional teams.
Attention to detail and commitment to delivering high-quality work.
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