Lead Cloud Data Solutions Engineer – HR Systems (Banking)

Lead Cloud Data Solutions Engineer HR Systems (Banking)

Role Overview

As the Lead Data Solution Engineer within the Data Strategy team you will architect and deliver enterprise-scale data solutions that drive innovation and efficiency across HR processes.

This role combines deep technical hands-on expertise in data engineering data architecture and data modeling with strategic leadership to align data systems with HR business objectives. You will lead cross-functional teams mentor engineers and ensure compliance with regulatory standards in a highly governed environment.

Key Responsibilities

• Design and develop data models processes and systems ensuring alignment with business requirements and organizational standards and best practices.
  
• Provide hands-on technical leadership and deliver innovative data solutions that enhance operational efficiency and address complex business challenges.
  
• Lead end-to-end data solution design and implementation for HR systems ensuring scalability security and alignment with hybrid cloud strategy (Azure / AWS / On-Premises).
  
• Define and govern data architecture standards including:
  
• Enterprise data models
  
• Relational database design
  
• Metadata management for HR domains
  
• Build and optimize scalable ETL/ELT workflows using technologies such as:
  
• OpenShift
  
• Snowflake
  
• dbt
  
• Airflow
  
• Spark
  
• Focus on HR data integration across domains such as:
  
• Core HR
  
• Payroll
  
• Talent Management
  
• Drive DevOps and CI/CD practices to automate deployment pipelines and ensure high availability of HR data platforms.
  
• Collaborate with HR stakeholders and product managers to translate business requirements into technical solutions.
  
• Ensure compliance with data governance and regulatory frameworks including risk and privacy requirements.
  
• Mentor engineers and lead cross-functional teams consisting of developers business analysts and HR partners.
  
• Apply emerging technologies such as AI/LLM and advanced analytics to enhance HR data capabilities and innovation.
  

Required Qualifications & Experience

Education

• Bachelors degree in Computer Science Software Engineering or equivalent.
  

Professional Experience

• 10 years of experience in data architecture data engineering or enterprise data management.
  
• 6 years designing enterprise data architectures across multiple domains.
  
• 6 years designing and optimizing ETL/ELT and data integration solutions.
  
• 6 years working with data warehouses data lakes and analytics platforms.
  
• 6 years of experience with data modeling and relational database design.
  
• 5 years of hands-on experience with Snowflake or similar cloud data platforms.
  
• 5 years of hands-on experience with SQL Python Java or similar programming languages.
  
• 3 years of experience designing architecting or building data products.
  

Technical & Domain Skills

• Strong understanding of data governance frameworks.
  
• Strong knowledge of data quality methodologies and metadata management.
  
• Experience working in highly regulated industries particularly banking or financial services.
  
• Experience designing scalable secure and high-performance data solutions.
  
• Strong understanding of enterprise data architecture data integration and data engineering best practices.
  
• Experience with cloud and hybrid data environments including Azure AWS and on-premises infrastructure.
  
• Strong technical leadership mentoring and cross-functional collaboration skills.
  

Key Technology Stack

Core Competencies

• Enterprise Data Architecture
  
• Data Engineering
  
• Data Modeling
  
• Data Integration
  
• ETL/ELT
  
• Cloud Data Platforms
  
• Data Warehousing & Data Lakes
  
• Data Governance
  
• Metadata Management
  
• Data Quality
  
• HR Data Integration
  
• DevOps & CI/CD
  
• Technical Leadership
  
• Cross-Functional Team Leadership
  
• Regulatory Compliance