Data Pipeline & Ingestion Engineer

PeerIslands

1d

About The Position

The Operational Data Layer (ODL) program is a large-scale data-platform build for a leading benefits administration platform. The platform ingests data from multiple legacy benefits systems, masters it into golden records, transforms it into a canonical data model, and serves it through modern APIs — built on an AWS / Java / Kafka stack in a HIPAA/SOX-regulated benefits domain spanning health, wealth/401(k), spending accounts, and leaves.

You will build and operate the data backbone of ODL: bulk and streaming ingestion from legacy source systems, medallion-layered storage (Bronze/Silver/Gold), identity resolution and golden-record consolidation, source-to-canonical mapping and crosswalks, and the data-quality and reconciliation gates that prove data is complete and correct before it is published. This is the volume engine of the program — every new client onboarded flows through the pipelines you build.

Requirements

• 5+ years building production data pipelines at scale
• Kafka depth: consumers/producers, replay, DLQ, exactly-once / idempotent processing patterns
• Strong SQL and solid ETL fundamentals
• Java and/or Python in production
• Medallion / lakehouse layering, CDC, watermark/checkpoint patterns, and batch–stream hand-off
• Data-quality frameworks: validation rules, quarantine and re-entry, quality scoring, reconciliation
• Entity resolution / MDM exposure: record matching, dedup, survivorship — via commercial tools (Informatica MDM, Reltio) or custom builds
• Data mapping and crosswalk discipline: profiling messy datasets, authoring governed reference data, config-as-code (YAML/JSON, Git)

Nice To Haves

• Probabilistic record linkage at depth — blocking/candidate generation, scoring models, threshold calibration (expected at senior level)
• Schema registry experience (Avro/Protobuf)
• Extracting from mainframe or older RDBMS sources with limited CDC support
• Financial reconciliation in finance-adjacent domains
• Benefits administration or healthcare domain knowledge

Responsibilities

• Build batch-seed and event-tail ingestion per source system, including seed→tail watermark hand-off, idempotent upserts, and dedup ledgers
• Build and operate medallion layers with reprocess-from-Bronze, pipeline orchestration (checkpoints, retry/backoff, DLQ), and full observability
• Build data-quality gates (quarantine / pass-with-flag), quality scoring, and a reconciliation engine covering count, record, and financial reconciliation — financial is zero-tolerance
• Build identity matching combining deterministic rules with probabilistic scoring and confidence bands; deliver deduplication, golden-record materialization, and survivorship rules, calibrating match thresholds with labelled data
• Author and maintain source→canonical structural mappings and value crosswalks (e.g., collapsing 1,800+ raw employment-status values to ~20 standard ones) as governed, versioned configuration
• Enforce data contracts at the boundary: schema registry, fail-fast validation, and semver-compatible schema evolution

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed