Ab Initio Developer

1) Ab Initio core development (expert)· GDE proficiency: designs and builds complex graphs end-to-end; strong command of component configuration, metadata propagation, partitioning, and checkpointing.· Reusable framework mindset: parameterized graphs, shared subgraphs, reusable transform components, standardized logging/error handling patterns.· Programming in transforms: strong use of DML, XFR, and embedded scripting where used; can write efficient expressions and avoid costly per-record logic.· Metadata discipline: robust record formats, strict typing, handling of optional/nullable fields, encoding/locale concerns, and schema evolution strategy.2) Performance engineering & scalability (expert)· Parallelism & partitioning ; chooses partition keys intentionally; understands hash/range/round-robin/broadcast; avoids skew and hot partitions.· Sort/join/aggregate optimization: picks correct join strategies, minimizes re-sorts, uses flow tuning and component alternatives (e.g., lookup vs join) appropriately.· Memory/I/O awareness: understands spill behavior, buffer sizing concepts, file system throughput, and impacts of compression and record sizes.· Benchmarking: can baseline runtime, identify bottlenecks, and improve throughput while preserving correctness.3) Data engineering fundamentals (expert)· ETL design: incremental vs full loads, CDC patterns (where applicable), late-arriving data handling, idempotent re-runs.· Data quality: profiling, validation rules, reconciliations, thresholding, and actionable rejects (not silent drops).· Lineage & audit: column-level mapping clarity, control totals, and traceable transformations for regulated reporting.4) Platform & operational mastery (strong senior)· Scheduling/orchestration: integrates with enterprise schedulers; understands dependencies, calendars, rerun semantics, and backfills.· Error handling: standardized reject paths, quarantines, retries, alerting hooks, and operational dashboards/log patterns.· Restartability: checkpointing, safe partial reruns, and consistent handling of intermediate datasets.5) Environment, deployment, and CI/CD (strong)· Promotion discipline: dev/test/prod migration practices, parameter separation, secrets/config externalization.· Version control: EME/metadata repo practices and Git integration patterns where applicable; controlled releases with rollback.· Packaging: reproducible deployments of graphs, scripts, metadata, and configuration bundles.6) Data stores & interfaces (strong)· Files: fixed/variable, delimited, binary, mainframe formats (EBCDIC/COBOL copybooks) if relevant; compression and encryption handling.· Databases: strong SQL; bulk load/unload patterns; transaction boundaries and batching.· Messaging/streams (if used): conceptual ability to incorporate Kafka/queues, but only if present in the stack.7) Security, controls, and compliance (non-negotiable)· PII handling: masking/tokenization in lower envs, secure landing zones, least privilege access patterns.· Controls: audit trails, approvals, and evidence generation for data pipelines; operational sign-off artifacts when required.· Secrets: no credentials in graphs; managed secrets and rotation patterns.