Tech Lead

at  Delivery centric Technologies

EXPERIENCE: 6+ YEARS

Job Description: This role intersects analytics, systems, and project delivery, providing thought leadership and innovation for analytical data. The primary responsibility is the extraction, transformation, and creation of analytically ready data for use in descriptive, diagnostic, predictive, and prescriptive analytics. This includes the effective and efficient build and management of data deliverables, encompassing design, development, documentation, support, and maintenance.

PREFERRED SKILLS:

• Deep understanding of Banking Products, processes, and data sources, with expertise in credit risk.
• Excellent written and verbal communication skills to effectively understand business needs and communicate actionable insights and results.
• Strong collaboration skills to work with Risk Analytics colleagues and other departments (e.g., Product Management, Customer Insights, Collections, and Fraud) on cross-functional projects.

ABOUT US:

We are Delivery Centric, a dynamic technology company that is transforming the delivery of cloud implementations and Cyber security. We are headquartered in Australia with a global presence. We are tenacious, future-thinking, and highly driven to achieve an ambitious vision to be the leading global provider of innovative technologies for companies that keep our world clean, safe, and secure.
Our fast-paced and supportive environment will offer you lots of benefits, including a competitive salary, a friendly team, a healthy work environment, and opportunities for training and development

Why work with us?

• Work with diverse technologies, projects, clients and industries.
• Spend your days in a creative and innovative environment.
• Share experience and knowledge as part of an agile and dynamic team

APPLY NOW or share your resume to smruthi.suresh@deliverycentric.com
Job Type: Full-time

Work Authorisation:

• Australia (Preferred)

KEY RESPONSIBILITIES:

• Collaborate with business units to understand credit risk-related data elements, including identifying relevant reference data, metadata, and data lineage.
• Analyze source system data and identify derived measures used by the business.
• Develop data definitions and publish data.
• Identify optimal sources for required data variables (e.g., for modeling, calculation, and reporting).
• Investigate data to determine root causes of issues and develop necessary business rules.
• Develop analytical data routines for extraction, alignment, transformation, and preparation for analytical consumption.
• Engineer, design, and optimize data processes within the Analytics Data Layer.