About Infinitive: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."
Role OverviewWe are seeking a highly technical Ab Initio Subject Matter Expert who can do more than develop or maintain graphs. This role requires someone who deeply understands how Ab Initio works, including GDE 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.
Key ResponsibilitiesAb Initio Graph Analysis & Reverse EngineeringAnalyze 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
Technical Translation & DocumentationTranslate 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 it and how to preserve the same business outcome in a new implementation.
Business Logic InterpretationPartner 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.
Metadata, Lineage & Dependency DiscoveryUse 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
Migration & Modernization SupportSupport initiatives to recreate or migrate Ab Initio logic to modern platforms such as Databricks, Spark, Snowflake, cloud-native data pipelines, or other enterprise data platforms.
Work closely with migration teams to ensure the new implementation preserves the intent, business rules, control logic, and data outcomes of the original Ab Initio process.
Help determine where to modernize, simplify, optimize, or redesign versus where to perform a like-for-like translation.
Performance & Operational UnderstandingAnalyze graph design, execution patterns, partitioning strategies, data volumes, component usage, and runtime behavior to identify performance bottlenecks or operational risks.
Interpret logs, job failures, restart logic, dependencies, Control Center executions, and environmental scripts to understand how processes run in production.
Mentorship & StandardsProvide guidance to development, migration, and QA teams on Ab Initio best practices, graph interpretation, reusable components, metadata management, testing, and documentation standards.
Help establish repeatable patterns for Ab Initio assessment, documentation, reverse engineering, and migration readiness.
Required Experience & SkillsCore Ab Initio Expertise- 7+ years of hands-on Ab Initio experience in complex enterprise environments
- Deep knowledge of GDE, Co>Operating System, EME, Control Center, DML, XFR, plans, sandboxes, multifile systems, and reusable components
- Ability to read, interpret, and explain complex Ab Initio graphs without relying only on original developers
- Strong understanding of batch processing, parallelism, partitioning, component behavior, metadata, and dependency management
- Experience with production support, scheduling, logs, restarts, and operational controls
Graph Translation & Reverse Engineering- Proven experience deconstructing legacy Ab Initio applications and documenting functional logic
- Ability to identify business rules embedded in transformations, joins, lookups, filters, and aggregations
- Strong source-to-target mapping skills
- Ability to convert technical graph logic into clear specifications for recreation, modernization, or migration
- Experience working with incomplete documentation and legacy systems where knowledge may be tribal or fragmented
Data & Engineering Skills- Strong SQL skills with experience analyzing large datasets
- Experience with enterprise data warehouses or data platforms such as Teradata, Oracle, Snowflake, Hadoop, or Databricks
- Strong Unix/Linux skills, including shell scripting with KSH, Bash, or similar
- Familiarity with job orchestration, file movement, batch controls, data reconciliation, and exception handling
- Ability to compare source and target outputs and support functional validation
Business & Communication Skills- Ability to explain complex technical logic to non-technical stakeholders
- Strong documentation, communication, and analytical skills
- Comfortable working with business teams to validate process intent and expected outcomes
- Ability to bridge legacy engineering teams, modern data engineering teams, QA teams, and business stakeholders
- Strong problem-solving mindset with the ability to work through ambiguity
Preferred Qualifications- Experience in Financial Services, Banking, Capital Markets, Insurance, or other highly regulated industries
- Experience supporting migration from Ab Initio to Databricks, Spark, Snowflake, cloud platforms, or modern data engineering frameworks
- Knowledge of AWS, Azure, or Google Cloud Platform data environments
- Experience with Ab Initio Metadata Hub, Acquire>It, Query>It, Continuous Flows, ICFF, or meta-programming
- Understanding of data governance, lineage, auditability, and regulatory reporting requirements
- Familiarity with financial services data domains such as customer, account, transaction, payments, risk, AML, KYC, fraud, finance, or regulatory reporting
- Experience creating migration assessment documents, graph inventories, complexity scoring, and modernization roadmaps
Infinitive is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.
Infinitive is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $124,000 - $190,00.00.
