Responsibilities
- Assess existing data ingestion pipelines, storage structures, data models, and batch processing dependencies
- Identify root causes of recurring data quality issues, lineage gaps, and downstream performance bottlenecks
- Design a scalable, layered data architecture supporting raw ingestion, standardized data, and curated consumer-aligned datasets
- Define canonical data models to standardize heterogeneous partner data across formats
- Recommend and apply appropriate modeling approaches, including dimensional, Data Vault, normalized, or hybrid models
- Establish data validation, enrichment, and transformation patterns that improve reliability and consistency
- Define data quality rules, validation checkpoints, naming conventions, and metadata standards
- Design data contracts and schema evolution strategies to support partners onboarding and backward compatibility
- Establish governance and ownership models, including data stewardship and accountability frameworks
- Define metadata management, lineage tracking, observability, and lifecycle management standards
- Conduct structured gap analysis between current and target states
- Develop a phased migration roadmap that minimizes operational risk and stabilizes downstream batch ecosystems
- Provide implementation recommendations across people, process, tooling, and governance
Required Experience
- Advanced expertise in logical and physical data modeling across structured and semi-structured data
- Strong experience designing canonical data models and standardization strategies
- Deep understanding of dimensional modeling, including star and snowflake schemas
- Practical knowledge of Data Vault and hybrid modeling approaches
- Experience transforming legacy data platforms into modern data lake or lakehouse ecosystems
- Proven track record addressing systemic data quality issues at scale
- Experience designing ingestion frameworks for heterogeneous data sources
- Strong grasp of metadata management, lineage, and observability concepts
- Experience defining governance models and stewardship frameworks
- Demonstrated ability to conduct structured assessments, gap analysis, and roadmap development
- Strong stakeholder engagement and architectural communication skills
Preferred Experience
- Experience leading enterprise-scale data modernization initiatives
- Demonstrated success in stabilizing downstream batch ecosystems through improved modeling and governance
- Experience delivering phased migration roadmaps in complex, multi-partner data environments
- Experience supporting healthcare payer data domains such as claims, enrollment, providers, or quality reporting
Top Skills
What We Do
Doran Jones Inc. (DJI) is the leading financial services Data Engineering and Application Development firm, specializing in Capital Markets, Risk, and Regulatory Compliance. We are US-based, helping our clients fill gaps in capacity and expertise, reduce risk, and accelerate change. Our leaders average over 25 years of experience in Financial Services and Technology. DJI is repeatedly engaged by the largest and most complex clients for our Agile transformation expertise and practical understanding of the critical relationship between data, architecture, and application development.
DJI has a mission to place more people from non-traditional backgrounds into sustainable technology careers. Through partnerships with non-profit technology programs in underserved communities and Veteran organizations, candidates transition from tech training programs into real IT careers at DJI. Our unique recruitment policy allows us to create exceptional teams, bringing a broad spectrum of experience to our company and creating anything but a traditional consulting firm.
DJI is a wholly-owned subsidiary of McLaren Strategic Ventures, a private equity firm, that invests in start-ups and scale-ups. They provide a full range of highly trusted domain consulting, advisory services, and innovative technologies globally. Doran Jones is able to offer a broad range of technology, deeper AI and machine learning tools, data intelligence, alternative resourcing capabilities, and capital access to invest and digitize at scale. Our clients benefit from this unique portfolio allowing them to accelerate the pace of their own digital transformations through innovative products and services designed around industry-wide issues.
