Data Engineer
Summary
Leads design and delivery of cloud-based data platforms using AWS services like Redshift, Glue, and PySpark, ensuring scalable, secure data solutions for analytics and governance.
Data Technical Lead plays a pivotal role within our evolving Data organization, leading the solution design, development, and strategic implementation of data solutions. The candidate will be responsible for driving execution of cloud-based data architectures, ensuring the platform’s scalability, security, and performance while addressing both business and technical
requirements. This role demands a hands‑on leader with deep technical expertise who can also steer strategic initiatives to success.
- Collaborate with the Product Owner in the writing and prioritization of technical user stories and enablers in the product backlog.
- Work with Scrum Master and Product Owner to resolve and elevate technical impediments.
- Participate in team‑level agile ceremonies, like backlog refinement, sprint planning, daily standups, iteration demos and retrospectives.
- Provide technical and development guidance to team members daily (e.g. set direction on technical solutioning, support code fixes, technical release planning, etc.)
- Burn user stories from the sprint backlog to deliver on the team's iteration goals
- Create and maintain technical documentation, such as design documents, technical roadmaps, etc.
- Engage with subject‑matter experts across the organization when they are required for user story development
- Spearhead the solution design, development, and delivery of data solutions using AWS core data services, driving innovation in Data Engineering, Governance, Integration, and Virtualization.
- Oversee all technical aspects of data systems, ensuring end‑to‑end delivery from proof‑of‑concept (PoC) to production deployment.
- Continuously enhance the data platform delivery efficiency to improve performance, resiliency, scalability, and security while incorporating new data technologies and methodologies.
- Work closely with business partners, data architects, and cross‑functional teams to translate complex business requirements into technical solutions.
- Develop and implement data management strategies, like, Data Warehousing, Master Data Management, and Advanced Analytics solutions.
- Combine technical solutioning with hands‑on work as needed, actively contributing to the architecture, coding, and deploying critical data systems.
- Ensure system health by monitoring platform performance, identifying potential issues, and taking preventive or corrective measures as needed.
- Be accountable for the accuracy, consistency, and overall quality of the data used in various applications and analytical processes.
Qualifications:
- Must have a Bachelor of Science of computer related courses, eg. Information Technology, Computer Science, Management courses with major in computer studies.
- At least 12 years of strong hands‑on experience in developing and delivering Data Solutions, with a strong background in AWS Cloud Platform.
- Proven experience in designing and implementing AWS data services (such as S3, Redshift, Athena, Glue, Python, PySpark.) and a solid understanding of data service design patterns.
- Expertise in building large‑scale data platforms, including Data Lakehouse, Data Warehouse, Master Data Management, and Advanced Analytics systems.
- Demonstrated experience managing multiple projects in a high‑pressure environment, ensuring timely and high‑quality delivery.
- Strong problem‑solving skills, with the ability to make data‑driven decisions and approach challenges methodically.
- Proficiency in data solution coding, ensuring access and integration for analytical and decision‑making processes.
- Good verbal & written communication skills and ability to work independently as well as in a team environment providing structure in ambiguous situation.
- Ability to effectively communicate complex technical solutions to both technical and non technical stakeholders.
- Experience working with multi-disciplinary teams and aligning data strategies with business objectives.
- Must have full scale development experienced and able to successfully implemented an enterprise wide Data Warehouse using AWS Cloud Platform, AWS DMS, Glue, Python, PySpark, Reddshift