A2Z Sync

A2Z Sync

A2Z Sync provides Dealership Desking, Menu & F&I Centralized Dealership Desking Tools, F&I and Menu software for automotive dealerships. Their platform enables automotive groups to transact faster with higher profitability, simplifying the car buying e...

Internet Software & Services
51-250
Founded 2017

Description

  • Own the end-to-end data platform, including Bronze, Silver, and Gold layers, the Feature Store, and the Action Ledger.
  • Design and implement feature store architecture for online low-latency serving and offline point-in-time training joins.
  • Build the model data pipeline that prepares features, assembles training data, and supports SageMaker and Bedrock workloads.
  • Define and execute the legacy data migration strategy, including table placement, dual-write validation, and zero-downtime cutover patterns.
  • Create and operate automated data quality and anomaly detection for schema drift, null spikes, freshness issues, and inconsistent integrations.
  • Establish data governance controls for retention, PII handling, audit integrity, and multi-tenant AI governance.
  • Design streaming and event-driven data flows using DynamoDB Streams, EventBridge, CDC, and real-time feature materialization.
  • Publish data architecture documentation, canonical entity schemas, and optimization-function data contracts.
  • Collaborate cross-functionally on optimization-function data modeling, feature catalogs, and approval-gateway integrations.
  • Review critical-path SQL, pipelines, schemas, and pull requests with strong implementation rigor.

Requirements

  • 7+ years of experience in data engineering or data architecture, including at least 2 years in a platform architect or Head-of role.
  • Deep experience with relational and NoSQL modeling, including MySQL, PostgreSQL, Aurora, DynamoDB, and DynamoDB Streams.
  • Hands-on experience building or operating feature stores with online serving, offline training, point-in-time correctness, and freshness SLAs.
  • Hands-on experience with AWS data and ML services such as Glue, Athena, S3, DynamoDB, Lake Formation, Aurora, and SageMaker.
  • Current hands-on experience preparing data for LLMs, embeddings, or ML models in production.
  • Experience with streaming and CDC patterns such as DynamoDB Streams, Kinesis, EventBridge, or Kafka.
  • Experience with data pipeline orchestration tools such as NiFi, Airflow, or Step Functions.
  • Experience with data migration patterns including dual-write, CDC, reconciliation validation, and zero-downtime cutover.
  • Experience with multi-tenant data architectures and trade-offs such as database-per-tenant, schema-per-tenant, and row-level security.
  • Strong data governance discipline covering retention, PII handling, audit trails, cost attribution, and enforceable controls.
  • Ability to write unambiguous data architecture documents and step in to write SQL or pipeline code when needed.
  • Hands-on experience with SageMaker model lifecycle tooling such as training pipelines, model registry, Model Monitor, and drift response.
  • Hands-on experience with AWS Bedrock, including Knowledge Bases, model invocation, guardrails, and production deployment.
  • Experience building embeddings pipelines or retrieval systems for semantic search, recommendations, or RAG.
  • Experience building closed-loop data systems with action telemetry, outcome attribution, A/B holdouts, and lift measurement.
  • Experience with data quality and anomaly detection at scale, including feature/training skew and freshness monitoring.
  • Understanding of multi-tenant AI governance, including PII redaction, tenant-scoped inference, per-dealer routing, cost attribution, and audit logging.
  • Nice to have experience in automotive, fintech, or multi-tenant marketplace data environments.
  • Nice to have familiarity with third-party dealer data providers and formats such as CDK, DealerTrack, Tekion, SOAP/XML, REST, JSON, and email.
  • Nice to have experience with constrained optimization, assignment problems, or scheduling solvers.
  • Nice to have experience with vector databases such as OpenSearch or Pinecone.
  • Nice to have experience with open table formats such as Iceberg or Delta Lake.

Benefits

  • Comprehensive medical, dental, and vision coverage.
  • Employer-provided STD/LTD and life insurance.
  • Matching 401(k) plan.
  • Unlimited paid time off, including 10 paid holidays.
  • Fun, casual, and collaborative culture.
  • Opportunity to own a high-stakes AI/data platform roadmap and architecture decisions.
  • Meaningful impact on customer outcomes and dealer profitability.

Interested in this position?

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