Tech Lead - Data Modeling Job

Experience

Job Summary:

We are looking for a seasoned Data Modeler with 8-10 years of experience in enterprise data modelling, Source-to-Target (ST) mapping, and data profiling. The ideal candidate will be responsible for designing scalable data models, ensuring data quality, and collaborating across teams to support business intelligence and analytics initiatives.

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.

Required Technical/ Functional Competencies

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:

• Specializedknowledge 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:

• Specializedknowledge 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.

Required Behavioral Competencies

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.

Certifications