Data Migration & Batch Engineer

Data Migration & Batch EngineerLocation: Charlotte, NC/ Austin, TX / San Diego , CA and NYC/ NYType: ContractExperience: 8+ years in relational data migration and/or ETL engineering, with cutovers delivered to production.You own the deterministic core of the database and batch workstreams. Two systems have minted identifiers independently for many years across about a million accounts; merging them incorrectly mis-maps an investor's assets. This seat is where correctness is defended.ResponsibilitiesOwn schema-drift detection and reconciliation (Red Gate / SQL comparison) - the deterministic ground truth on which every downstream decision rests.Build the deterministic rule ladder for table and job dispositions: staging / truncate-and-reload detection, dead-table detection, target-equivalent matching, straight-through repoint, duplicate-job merge.Own the ID-collision engine: a full (never sampled) overlap scan across every shared ID space; classification into true collision, phantom and historical overlap; analysis of the resolution strategy; and a non-bypassable validation harness on every script that touches an ID column.Own data reconciliation: row counts, column checksums, referential integrity, stored-procedure output parity, business-key parity; staging promotion gates and validated rollback scripts.Batch: build the dependency graph, blast-radius (butterfly) scoring, Simple/Medium/Complex classification, and the migration approach per job.Own the SLA validation harness - proving every migrated job and every SLA chain runs within its window under combined nightly volume.Emit the downstream artifacts: migration scripts, job modifications, rollback scripts, reconciliation specifications.QualificationsSQL Server (2024) - deep: DDL, stored procedures, indexing, referential integrity, query performance.Relational data migration at scale - Red Gate, AWS DMS or equivalent; cutover, reconciliation and rollback delivered in production.Identity and key-collision resolution - surrogate versus natural keys, reconciliation and historical-mapping tables, preserving referential integrity under a merge. Rare, and highly valued for this role.Informatica PowerCenter; ETL dependency analysis; SLA and batch-window modelling.Python and strong SQL; data-quality and validation frameworks.The discipline to keep correctness-critical steps deterministic while working alongside an LLM reasoning layer.Working knowledgeInformatica IDMC and/or Apache Airflow; PySpark.Graph queries; handling of regulated / PII data.