AVP - Technology - Data Engineer.MGN Pak - TECH - Data Management.MIT

• Principal/Lead Data Engineer will design & maintain data pipelines of real time and batch, creates data strategy, data architecture, best practices and who can lead the organization in making strategical improvements in the Data Analytics engineering solutions.
• Proficient in understanding customer business needs and mapping them to technology, be it custom development or infrastructure deployment, and having the ability to manage complex projects in a structured and streamlined way within project KPIs and with superior customer experience.
• Candidate will be responsible for leading the Data Engineering team teams and expanding data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. 
• Looking for professional who is fit for below purpose:
• Domain Expertise: Should have strong functional knowledge in the banking domain; areas include Retail, Corporate, Risk and Regulatory, Core Banking, Treasury and Derivatives.
• Data Architect/Modeler: Expertise in building scalable Enterprise Products/ Applications and skillful in architecture. Lead the construction and maintenance of an automated, scalable, resilient, and self-healing data platform.
• Decision Support: Should collaborate with cross functional teams and senior management to provide data driven recommendations that inform strategic decision making and business planning.
• Data Quality and Governance: Ensure data accuracy, consistency, and integrity throughout the data analysis process. Implement and adhere to data governance policies.
• Leadership: Provide mentorship and guidance to junior analysts, encouraging their professional growth and fostering a collaborative team environment.
• Continuous Improvement: Identify opportunities for process improvement, automation, and optimization with the data analytics function.

Project Management: Lead and manage data analysis projects from inception to completion, ensuring timely delivery of high-quality results.

• Customer, Financial & Regulatory Delivery
  • Experienced at creating data models, using new age technologies, and analyzing data mining algorithms to deliver insights and implement action-oriented solutions to complex business problems.
  • Should have experience on building Enterprise Solution Architect for Big Data Solution to derive usage of Big Data as Central Data & KPI Repository for all analytical and reporting requirement of work.
  • Designs and Develops Data domains across banking products and lays foundation for Data domain architecture. Building domain centric framework around Customer 360 covering products, transactions etc.
  • Proficient in requirement gathering, finalizing scope, consensus building across diverse stakeholders, formulating BRD’s, concluding UAT, demos and trainings, tracking Agile Scrum & rituals.
  • Data Orchestration and Data-Ops practices enabler for the team.
  • Enabling data driven solution with new age technology for transformation initiatives.
  • Interpret the requirements of various big data analytic use cases and scenarios and drive the design and implementation of specific data models to ultimately help drive better business decisions through insights.
  • Develop necessary enablers and data platform in the big data lake environment and has the responsibility of maintaining its integrity during the life cycle phases.
  • Build strategy and design for hybrid data architecture covering all business groups as per their respective regulatory guidelines.
  • Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  • Ensuring timely delivery of all KPI’s as per defined project timelines

• Risk & Governance
  • Work closely with the development team to assess and review technical debt, NFRs.
  • Data Quality - Ensure data accuracy, consistency, and integrity throughout the data analysis process.
  • Enabling tools & QC framework to ensure no data loss while presenting data output in the form of UI.
• BAU, Production Resilience & Availability 
  • Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
  • Data flows for ingestion, normalization, and transmission of data from various complex core banking data sources in different standard and proprietary formats.
  • Optimize existing data flows to improve the performance and reliability of our system.
  • Regular health checks up and enabling alerts to reduce failures/job delays.
  • Defining the Change Governance Process by adopting Standard CR, Pre-defined CR principles. 

• Stakeholder, Vendor & People Management:
  • Developed a string connection with business stakeholders based on transparent proactive communication and flawless timely deliveries.
  • Working closely with Product Management team to define the product solution roadmap.
  • Work closely with the development team to assess and review design solutions and technical rationalization.
  • Worked closely with Organization level Transversal Technical Architecture team to assess and review the product roadmap.
  • Manage the Data Analytics & Engineer Team and practices across the domain. 
  • Vendor Managements:  Managing relationships with partner vendors and service providers, evaluating their performances and ensuring adherence to service level agreements ( SLA). Manage the Data Analytics & Engineer Team and practices across the domain.
  • People management responsibilities encompass the tasks and activities involved in leading, guiding, and developing a team of individuals to achieve organizational goals effectively.
  • Setting clear performance expectations, conducting regular performance reviews, providing feedback, and offering guidance on areas of improvement.
  • Involve in coaching, mentoring, continuously push, encourage, team to produce their best work. 
  • Good & effective communication with team by providing business visions along with their interpersonal growth.
  • Effective tech & ice-breaking sessions to enhance their personal growth and aligned with overall business goals and vision.

• Innovation & Collaboration: 
  • Working closely with cross-functional teams, including IT, business leaders, and stakeholders, to understand data requirements and deliver effective data solutions.
  • Staying updated with the latest trends and advancements in data technologies and proposing innovative solutions to improve data architecture and engineering processes.
  • Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
  • Exploring the Automation opportunities that would help in increasing the Time to Market, Faster SDLC process.

Improving product value and focus should be on business benefits, ROI, and cost reduction.

Experience:

• Principal Data engineer with a solid technical background and experience in data-intensive Corporate, Retail & Investment Banking systems (> 13 years).
• Experienced in application designing, architecting, development and deployment using Big Data technologies & cloud concepts.
• Strong experience in Big Data, Hadoop Ecosystem, Spark, Python, SQL, Hive, Databricks, Big Query, Cloud concepts.
• 10+ years’ experience in data crunching from top-tier consulting, banking, private equity, or strategy/business role for a fast-growing global tech Company.
• 4+ years of experience in working with any of the Core Banking Systems like Oracle Flex cube (Preferred), Finacle, T24, TYS Prime etc.
• 4+ years of experience in working with any of the other banking systems like Customer Relationship Management, Document Management, Application workflow management etc. 
• Strong aptitude to quickly learn and adapt to newer technologies and technology change.

Core Skills:

• Big Data Engineering & SQL Concepts
• Data Analytics & Data Management Fundamentals
• Data Architect, Modelling, Governance
• Domain Knowledge in Banking/Finance area
• Team Management
• DevOps & Agile Methodology
• Cloud Powered Platform 
• Leadership & Communication Skills
• Workflow Management Tool
• Data Streaming solutions.