Tech Lead - Data Modeling Job

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Skills

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We are looking forward to hire Data Modeling Professionals in the following areas :

Experience

Job Summary:

Key Responsibilities:

• Develop and maintain conceptual, logical, and physical data models.
• Perform Source-to-Target (ST) mapping for data integration and transformation.
• Conduct data profiling to evaluate data quality, completeness, and consistency.
• Collaborate with stakeholders to gather requirements and translate them into data models.
• Ensure alignment with enterprise architecture and data governance standards.
• Document metadata, data lineage, and transformation logic.
• Support ETL/ELT teams with data mapping and modeling guidance.
• Participate in data quality initiatives and resolve data-related issues.
  

Technical Skills Required:

• 8–10 years of experience in data modeling, data architecture, or related roles.
• Expertise in ST mapping and data profiling.
• Strong SQL skills and understanding of relational and dimensional modeling.
• Preferred experience with cloud data platforms such as Snowflake.
• Familiarity with ETL/ELT processes, data integration, and data warehousing.
  

Soft Skills Required:

• Analytical Thinking: Ability to interpret complex data requirements and translate them into effective models.
• Communication Skills: Strong verbal and written communication to interact with technical and non-technical stakeholders.
• Collaboration: Proven ability to work cross-functionally with business analysts, engineers, and leadership.
• Problem Solving: Aptitude for identifying data issues and proposing scalable solutions.
• Attention to Detail: Precision in data mapping, profiling, and documentation.
• Adaptability: Comfortable working in fast-paced environments with evolving priorities.
  

Domain/ Industry Knowledge:

• Working knowledge of customer's business processes and relevant technology platform or product.
• Able to analyze current-state and define to-be processes in collaboration with SME and present recommendations with tangible benefits.
  

Requirement Gathering And Analysis:

• Specialized knowledge of requirement management processes and requirement analysis processes, tools & methodologies.
• Extract requirements for complex scenarios and prototype independently.
• Identify modules impacted, features/functionalities impacted and arrive at high level estimates.
• Develop traceability matrix and identify transition requirements.
  

Product/ Technology Knowledge:

• Implement code or configure/customize products, drive adoption of industry standards and practices, and contribute to development of reusable assets and innovative solutions.
• Conduct technical sessions and knowledge sharing sessions, and work on complex modules independently.
• Analyze various frameworks/tools and present recommendations, contribute to development of training and certification material, and demonstrate thought leadership through whitepapers and webinars.
  

Architecture Tools And Frameworks:

• Specialized knowledge of architecture Industry tools & frameworks.
• Implement tools & framework in a complex scenario.
• Conduct tools & framework customization & tailoring workshop.
  

Architecture Concepts And Principles:

• Specialized knowledge of architectural elements, SDLC, methodologies & customer business/domain.
• Establish Architectural principles/ patterns and use advanced tools to capture and analyze system/ technical issues.
  

Analytics Solution Design:

• In Depth knowledge of statistical & machine learning techniques.
• Able to design analytical modelling approach for moderate-scale projects or for components of large-scale.
• Understand business requirements & constraints including potential trade-offs between speed & accuracy, maintains trends.
  

Tools & Platform Knowledge:

• Familiarity with the wide range of data science/analytics commercial and open source software tools, their constraints, advantages, disadvantages, areas of application and mainstream packages relevant to technical stages of data science/analytics projects.
• Intermediate to advanced skills in programming languages used for data science/analytics and ability to apply these for data acquisition, pre-processing, modelling and model deployment. Ability to interpret and modify existing scripts and conduct quality checks.
  

Accountability:

• Takes responsibility for and ensures accuracy of results and deadlines of the function and/or team and in completing own work.
  

Collaboration:

• Reaches out to others in team to ensure connections are made and team members are working together.
• Looks for ways to integrate work with other teams, identifying similarities and opportunities, making necessary changes in work to ensure successful integration.
  

Agility:

• Demonstrates openness to the possibilities that change presents and begins to plan for how role may change.
• Works with others to prepare for change.
  

Customer Focus:

• Identifies trends and patterns emerging from customer preferences and works towards customizing/ refining existing services to exceed customer needs and expectations.
  

Communication:

• Communicates well-organized ideas, information, and data to broad and diverse audiences across the Organization (through formal and informal presentations).
• Helps others identify their appropriate audience.
  

Drives Results:

• Sets realistic stretch goals for self & others and perseveres to follow through with resilience and remains calm in a crisis or stressful situation to exceed organization/client expectation.
  

Resolves Conflict:

• Identifies and understands the source of conflict, addresses, and overcomes.
  

Our Hyperlearning workplace is grounded upon four principles

• Flexible work arrangements, Free spirit, and emotional positivity
• Agile self-determination, trust, transparency, and open collaboration
• All Support needed for the realization of business goals,
• Stable employment with a great atmosphere and ethical corporate culture
  

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