The Value Maximizer · 10 hours ago
Senior Data Engineer
New Jersey, United States
Full-time
Hybrid
Mid, Senior Level
4+ years expThe Value Maximizer is a consulting and technology services firm, and they are seeking a hands-on Senior Data Engineer to build and operate data pipelines for MDM. The role involves engineering scalable ELT patterns using Azure, Snowflake, dbt, and Python, focusing on data quality, reliability, and audit-ready delivery.
Information Technology & Services
Responsibilities
Design and implement ingestion patterns from source systems into Snowflake (batch and incremental/CDC where applicable)
Build scalable landing/staging/curated layers with clear lineage and reprocessing strategies
Implement orchestration patterns on Azure (scheduling, parameterization, retries, idempotency)
Develop and maintain dbt models for:o canonical master entities and relationshipso standardization/enrichment transformationso exception/validation views and stewardship-ready outputs· Implement dbt best practices: modular models, tests, exposures, documentation, and CI checks
Implement data quality rules and automated tests (dbt tests + custom checks in Python where needed)
Create exception datasets/metrics to support stewardship queues and remediation
Build reconciliation routines (source vs curated counts, duplicate metrics, completeness/consistency trends)
Support match/merge workflows by producing standardized inputs (keys, standardized attributes, dedupe candidates)
Implement survivorship logic where defined (source priority, recency, completeness) or enable it through curated datasets
Produce "publish" datasets and change detection outputs for downstream consumption
Optimize Snowflake workloads (warehouse sizing, clustering strategies where relevant, query tuning, cost governance)
Build robust operational patterns backfills, re-runs, error handling, SLAs, data freshness checks
Implement monitoring for pipeline health, data freshness, DQ failures, and exception volumes
Create runbooks and operational playbooks for production support and hypercare
Participate in go-live cutover, hypercare triage, and transition to BAU support
Work closely with Data Architect, BSA/Data Analyst, Backend/UI teams, QA, and DevOps
Participate in sprint planning, code reviews, and architecture/design reviews
Maintain high-quality documentation and version control (Git-based workflow)
Qualification
Required
4-7 years of data engineering experience with strong hands-on delivery ownership
Strong expertise in Snowflake (modeling, performance tuning, cost control)
Strong expertise in dbt (models, tests, macros, documentation, CI)
Proficient in Python for pipeline utilities, validations, automation, and troubleshooting
Experience implementing data quality and production monitoring practices
Strong SQL (advanced joins, window functions, profiling, reconciliation)
Experience with GenAI is required
Bachelor's Degree in Computer Science or related science field or equivalent
Preferred
Experience with MDM / Master Data concepts (golden record, dedupe, survivorship, stewardship workflows)
Experience with Azure data ecosystem tools (ADF/Synapse/Functions/Key Vault/Monitoring)
Experience with event-driven publishing or change-data outputs for downstream systems
Exposure to regulated/audit-heavy delivery environments (traceability, approvals, evidence)
Company
The Value Maximizer
At The Value Maximizer, we empower businesses to unlock their full potential through cutting-edge AI-based platforms.
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase