Ab Initio Architect​/Subject Matter Expert

Infinitive is a data and AI consultancy that enables its clients to modernize, monetize and operationalize their data to create lasting and substantial value. . We possess deep industry and technology expertise to drive and sustain adoption of new capabilities. We match our people and personalities to our clients' culture while bringing the right mix of talent and skills to enable high return on investment.

Infinitive has been named “Best Small Firms to Work For” by Consulting Magazine 9 times most recently in 2026. Infinitive has also been named a Washington Post “Top Workplace”, Washington Business Journal “Best Places to Work”, and Virginia Business “Best Places to Work.”

We are seeking a highly technical

Ab Initio Subject Matter Expertwho can do more than develop or maintain graphs. This role requires someone who deeply understands how Ab Initio works, includingGDE graphs, DML, metadata, EME, Control Center, reusable components, and batch execution patterns, and can reverse-engineer what existing Ab Initio applications are actually doing.

The ideal candidate is a technical translator: someone who can analyze complex Ab Initio graphs, interpret the embedded business logic, explain the flow of data, and document the intent clearly enough for another engineering team to recreate, modernize, or migrate the functionality.

This role is especially important in environments where Ab Initio has become a legacy “black box” and the organization needs to understand, document, and potentially rebuild those processes on a modern data platform.

Analyze existing Ab Initio applications, graphs, plans, DML, XFRs, parameter sets, sandbox structures, and metadata to understand how data is sourced, transformed, validated, enriched, and delivered.

Deconstruct complex graph logic and identify:

• Source and target datasets
• Joins, lookups, filters, rollups, scans, partitions, sorts, and reformat logic
• Data quality rules and exception handling
• Business rules embedded in transformations
• Dependencies across graphs, components, schedules, and downstream consumers
• Restart, recovery, and operational control logic

Translate Ab Initio logic into clear technical documentation that can be used by data engineers, architects, migration teams, QA teams, and business stakeholders.

Create detailed artifacts such as:

• Source-to-target mappings
• DML and metadata interpretation summaries
• Graph logic walkthroughs
• Transformation rule documentation
• Dependency and lineage maps
• Functional specifications for graph recreation or migration
• Test scenarios and reconciliation rules

The goal is not simply to document what the graph does technically, but to explain why it does itand how to preserve the same business outcome in a new implementation.

Partner with business, data, risk, finance, operations, and technology stakeholders to understand the business purpose behind existing Ab Initio processes.

Be able to explain complex data flows in plain language, including how a graph supports reporting, reconciliation, customer processing, regulatory needs, risk controls, financial calculations, or operational workflows.

Use Ab Initio EME, Metadata Hub, Control Center, project repositories, scripts, schedules, logs, and related documentation to identify upstream and downstream impacts.

Support end-to-end lineage discovery across:

• Source systems
• Intermediate files
• Serial and multifile datasets
• DML records
• Lookup files
• Database tables
• Output feeds
• Downstream applications and reports

Support initiatives to recreate or migrate Ab Initio logic to…