The posting
About the Job
This role oversees and manages the ingestion framework to ingest data from various data sources for data analytics and AI purposes.
Detailed activities include: - Analyzing the data requirements across various entities, develop, implement and maintain data ingestion pipelines from source to data lake pipelines.
- Automating data validation steps and report generation.
- Automating codes/ scripts that can be repeatedly used across similar analytics and reporting requirements.
- Managing and ensuring accuracy and timeliness and automation solution in end to end data extraction and integration with analytics and management reporting system.
- Designing the jobs schedule in scheduling tools and developing the configuration files for job schedulers.
- Performing production L2 batch support after production deployment.
- Perform code review functions for applications / programs developed by team members.
- To be part of initiatives that brings data into the data lake and delivers insights.
- Monitor and measure performance to assure ongoing data ingestion is meeting the SLA and optimization of the ingestion process to manage the performance and the SLAs.
- Work effectively with other stakeholders such as data engineering team, IT team, etc.
- Troubleshoot MapReduce/Spark Jobs and do performance tuning in production environments.
- Independently develop and sustain technical knowledge, certifications, and skills.
- Effectively handling day-to-day assignments given moderate directions and supervision.
We are looking for people who: • Bachelor or Master Degree in Computer Science, Engineering, or similar relevant field.
• Working experience in data ingestion or data engineering with Hadoop tech stack for 8+ years.
• Proficient with Scala and PySpark.
• Hands-on experience on Spark framework and other distributed data processing frameworks like Hadoop Map-Reduce, Hive etc. • Proficient in ETL tools like Talend.
• Proficient in RDBMS databases such as Oracle, MySQL, MSSqlServer.
• Strong scripting skills in Linux environment and SQL.
• Expertise in Hadoop ecosystems.
• Hands-on Experience in Sqoop, Hive, Spark, Python, Scala is a must.
• Hands-on Experience in Job orchestration / Job schedulers like Autosys, Control-M
• Good to have working experience with one of the cloud platforms like AWS (Amazon Web Services), Microsoft Azure or Google Cloud Platform.
• Ability to plan and organize technical work and deliverables. Ability to follow guidelines and adhere to the established software development standards and conventions.
• Self-motivated and independent. Able to work with minimum supervision and to work well with stakeholders and project staff.
• Ability to prioritize and multi-task across numerous work streams.
• Strong interpersonal skills; ability to work on cross-functional teams. Strong verbal and written communication skills.
• Deep knowledge of best practices through relevant experience across data-related disciplines and technologies particularly for enterprise wide data architectures and data warehousing/BI.
• Demonstrated problem-solving skills. Ability to learn effectively and meet deadline.
How you succeed: • Champion and embody our Core Values in everyday tasks and interactions.
• Demonstrate high level of integrity and accountability.
• Take initiative to drive improvements and embrace change.
• Take accountability of business and regulatory compliance risks, implementing measures to mitigate them effectively.
• Keep abreast with industry trends, regulatory compliance, and emerging threats and technologies to understand and highlight potential concerns/ risks to safeguard our company proactively.
