Vomela is the force behind remarkable brand experiences. We help brands create the moments people remember, at the intersection of brands and culture, whether at major events, in retail spaces, across transportation fleets, or inside mailboxes. With more than 2,000 employees at 30+ locations across North America, the UK, and Europe, Vomela delivers end-to-end visual communications with unmatched scale, care, and craft. Since 1947, leading brands have trusted Vomela to bring ideas to life in ways that truly matter.  


Vomela

At Vomela our greatest asset is our people. As a full-service visual communications company, we are looking for creative and intellectual thinkers that work with our customers to create compelling brand solutions and foster meaningful connections. And while you're focused on creating big things for global and local brands, we will help you build a career you can be passionate about.Apply now to find your place at Vomela.Pay Range: $180 - 200k USDJob SummaryThe Principal Data Engineer is the highest-performing contributor on our data engineering team - the person who sets the technical bar, owns the data platform end to end, and delivers work that others study. You'll define and execute data strategy at the engineering level, operating as the technical point of the spear for how the organization builds, scales, and trusts its data. You write production code. You design the architecture. You solve the problems that block everyone else. You mentor without being asked, influence without authority, and deliver without handholding. You're a force multiplier and you're hungry to shape not just the platform, but the broader data strategy of the business.Microsoft Fabric is our data platform. This role is for someone genuinely energized by the Fabric ecosystem, who tracks its evolution closely and sees its breadth - Lakehouse's, Event streams, Semantic models, Notebooks, Pipelines, Direct Lake as an opportunity, not a constraint. If you're looking for a role where your technical judgment shapes the trajectory of the entire data organization, this is exactly it.
What You'll Do...Design and implement dimensional models, star schemas, and snowflake schemas with rigorBuild and maintain semantic models that serve as the single source of truth for business reportingImplement Slowly Changing Dimension (SCD) strategies appropriate to each domainOwn master data engineering: golden record patterns, source-of-record authority, cross-system identity resolutionEstablish and enforce data modeling standards across the teamDesign and operate real-time and near-real-time pipelines using streaming technologies (Kafka, Confluent Cloud, Fabric Eventstreams) — and know when streaming is the right answer and when it isn'tRelentlessly drive down data staleness in non-streaming scenarios through intelligent scheduling, incremental load optimization, and pipeline orchestration designOwn performance tuning across the full stack — query optimization, partition strategy, indexing, Delta table compaction, semantic model refresh efficiency, and Direct Lake readinessApply operational engineering discipline: pipeline observability, alerting, SLA definition, failure recovery, and capacity planningDesign and implement controls appropriate for sensitive data (financials, PII, HIPAA, etc.)ETL / ELT Pipeline DevelopmentBuild robust, scalable, observable pipelines — watermark-based incremental loads, CDC patterns, batch and streaming architecturesEnsure pipelines are idempotent, recoverable, and production-hardenedServe as the senior technical voice in code review — your approval carries weightReport & Analytics DeliveryTranslate business requirements into semantic models and report-layer artifacts that non-technical users can trust and navigateServe as the platform's primary technical interface across consumer groups: Power BI report builders needing trusted, well-modeled semantic layers; AI/ML developers needing governed, feature-ready data surfaces; application developers consuming data via SQL endpoints, REST APIs, or Direct LakeDefine and enforce data contracts — schema stability, access patterns, SLAs — for each consumer classOwn the developer experience of the platform: discoverability, documentation, and onboarding

Requirements

RequiredMicrosoft Fabric: Lakehouses, Notebooks, Dataflows Gen2, Event streams, Semantic Models, Direct Lake modePower BI: report development, dataset/semantic model design, DAX proficiencySQL Server / Azure SQL/Postgres: query optimization, schema design, stored proceduresAzure DevOps: Git-based development workflows, CI/CD for data pipelines· Demonstrated use of AI coding assistants in a production engineering workflow· Ability to critically evaluate, edit, and improve AI-generated code and artifacts· Clear understanding of where AI accelerates work and where it introduces riskPreferred QualificationsFamiliarity with broader Azure Data Services (Azure Data Factory, Synapse Analytics, ADLS Gen2, Event Hubs) as complementary toolingExperience in a private equity-backed or multi-entity portfolio company environmentExposure to MDM platforms (Profisee, Semarchy, Ataccama, or equivalent)Experience with Confluent Cloud / Apache Kafka for streaming ingestion into Fabric or SynapseFamiliarity with cross-tenant Azure / Fabric architectureBackground in business analysis, solutions architecture, or pre-sales engineeringMicrosoft Fabric or Azure Data Engineer certifications

Benefits

Health Care Plan (Medical, Dental & Vision)Retirement Plan (401k)Life Insurance (Basic, Voluntary & AD&D)Paid Time OffShort Term & Long-Term DisabilityTraining & DevelopmentWellness Resources