Data Transformation Consultant

Job Title: Data Transformation Consultant

Interview: Virtual

Job Location: Remote

Job Duration: 6+ Months



Job Summary:

The Data Transformation Consultant partners with business and technical stakeholders to modernize and optimize enterprise data ecosystems. This role designs and delivers data transformation strategies, builds scalable data pipelines, and ensures data quality, governance, and performance to enable analytics, digital transformation, and data-driven decision-making.

Key Responsibilities:

• Engage stakeholders to understand data challenges, transformation goals, and success measures
• Define and deliver data transformation roadmaps aligned to enterprise architecture and business strategy
• Design, build, and optimize ETL/ELT pipelines across on-premises and cloud environments
• Transform, cleanse, and integrate structured and unstructured data from multiple source systems
• Develop scalable, reusable data models to support reporting, analytics, and AI/ML use cases
• Establish data quality standards, validation rules, and monitoring processes
• Support data governance initiatives including metadata, lineage, and master data management
• Ensure solutions meet security, compliance, and enterprise data policy requirements
• Lead workshops, contribute to solution design, documentation, and technical reviews
• Mentor junior team members and contribute to best practices and reusable assets

Required Qualifications:

• Bachelor s degree in Computer Science, Information Systems, Engineering, or related field
• 5+ years of experience in data transformation, data engineering, or analytics consulting
• Strong experience designing and implementing ETL/ELT solutions on modern data platforms
• Proficiency in SQL and one programming language (Python, Scala, or Java)
• Experience working with relational and non-relational data sources
• Strong consulting, problem-solving, and stakeholder communication skills

Preferred Qualifications:

• Experience with Azure, AWS, or Google Cloud
• Hands-on experience with tools such as dbt, Spark, Airflow, Fivetran, Informatica, or Talend
• Knowledge of data warehousing and lakehouse architectures
• Familiarity with DataOps/DevOps and CI/CD pipelines
• Experience supporting BI, analytics, or AI/ML workloads