Data Transformation Lead

Role Summary

The Data Transformation Lead is accountable for driving end‑to‑end data transformation initiatives—including cleansing, enrichment, modeling, validation, and migration—across cloud, MDM, analytics, and modernization programs. This role sits at the intersection of data engineering, governance, and business transformation, ensuring transformed data meets functional, quality, and compliance expectations. The Lead coordinates analysts, modelers, ETL developers, and platform SMEs to deliver clean, curated, and consumable data assets.

Key Responsibilities

• Lead Data Transformation Strategy & Execution
• Own and implement the data transformation approach, including cleansing, modeling, enrichment, and alignment to business logic. Define transformation pipelines and oversee execution across sprints—from raw to curated layers.
• Ensure transformation logic aligns with business rules, source-to-target mappings, and analytical needs.
• Oversee transformation layer design, ensuring standardized and governed patterns for data restructuring.
• Manage Cross‑Functional Data Teams
• Lead Data Analysts, Data Leads, Data Modelers, ETL Developers, DBAs, and other specialists in transformation-focused workstreams. Drive alignment between technical teams and business stakeholders to ensure the transformation meets business requirements.
• Review and sign off on transformation design, data models, ETL mappings, and quality checks.
• Data Cleansing, Profiling & Quality Oversight
• Oversee data cleansing activities, standardization, and business-rule validation.
• Run or guide data quality validation routines comparing legacy vs target systems to detect anomalies and improve accuracy. Establish root-cause analyses for transformation errors and lead remediation efforts.
• Ensure DQ rules, thresholds, and exception handling are embedded throughout transformation processes.
• Data Modeling & Architecture Alignment
• Guide the modeling of transformed datasets—including dimensional models, domain models, curated layers, and golden-record definitions. Validate mapping logic, transformation dependencies, lineage, and required enrichment attributes.
• Collaborate with data architects to ensure structure and standards align with cloud, MDM, or data warehouse strategies.
• Migration & Integration Support
• Support cloud/MDM migration cycles by ensuring all transformed data meets ingestion, validation, and cutover criteria. Validate transformed datasets against migration manuals, ETL specs, and modeling documents.
• Work with integration teams to ensure transformed data is ready for downstream publishing, APIs, or analytical consumption.
• Governance & Change Leadership
• Ensure alignment to organization-wide data governance, data policies, and compliance guidelines. Partner with governance teams to ensure transformed data meets stewardship and metadata requirements.
• Drive adoption of new transformation frameworks, standards, and best practices—consistent with transformation leadership expectations.
• Stakeholder & Program Management
• Communicate transformation progress, challenges, risks, and mitigation plans to program leadership.
• Run cross-functional workshops for business alignment, requirement clarification, and impact assessment.
• Enable collaboration between business process owners, technical SMEs, platform teams, and QA leads.
  
  

Technical Skills

Required Skills & Qualifications

• Strong experience in data transformation, including cleansing, enrichment, data modeling, and validation. Hands-on or oversight-level expertise in ETL/ELT workflows, data pipelines, and cloud migration processes.
• Experience with profiling, DQ tools, or custom validation routines. Understanding of dimensional modeling, data warehouse concepts, and metadata standards.
  
  

Leadership & Delivery Skills

• Proven ability to lead multi-disciplinary data teams.
• Experience managing complex data transformation efforts within modernization or migration programs.
• Strong ability to translate business rules into transformation logic and guide technical execution.
• Skilled in change management and driving adoption of new processes.
  
  

Preferred Experience

• Experience in cloud-based data platforms (Azure, AWS, GCP) or SaaS MDM transformations.
• Experience leading transformation streams within MDM, cloud migration, or data quality programs.
• Insurance, healthcare, or financial services domain knowledge is a plus.
  
  

Deliverables

• Transformation design documents
• Mapping/lineage artifacts
• Transformation validation and DQ reports
• Curated datasets and transformation layer outputs
• Issue and remediation logs
• Progress dashboards and stakeholder communications
  
  

Work model: Hybrid

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring 3-4 days a week in a client or Cognizant office in Jersey City NJ or Charlotte NC. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.

Salary And Other Compensation

Applications will be accepted until March 6, 2026.

The annual salary for this position is between $130,000- $150,000 USD depending on experience and other qualifications of the successful candidate.

This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.

Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan
  
  

Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law