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Open nowFirst seen 42 hours ago

Data Tech Lead

PM Consulting1,469 open roles

Where
Taguig, Metro Manila, Philippines, Metro Manila, Philippines
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Your applicationOpen nowData Tech LeadPM Consulting · Taguig, Metro Manila, Philippines, Metro Manila, Philippines

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market. PM Consulting postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 42 hours ago

PM Consulting median: 1 days open

The posting

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.

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.
  • 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

Responsibilities:

  • 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 escalate 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.); 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.
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