Principal Data Engineer

Vomela Company; Northern (KY); Hybrid; USD 180,000 - 200,000; Full time

Benefits offered by this job

Health care plan

401k retirement plan

Life insurance

Paid time off

Disability insurance

Training & development

Wellness resources

Job summary

Vomela Company is seeking a Principal Data Engineer to own the data platform end to end and set the technical bar across the organization. You will design architectures, write production code, mentor teammates, and shape the data strategy for the business.

You will work with Microsoft Fabric as the primary platform, build semantic models for trustable reporting, and drive real-time and batch data pipelines. A strong emphasis is placed on governance, data contracts, and sensitive-data controls.

Qualifications

• Microsoft Fabric: Lakehouses, Notebooks, Dataflows Gen2, Event streams, Semantic models, Direct Lake mode.
• Power BI: report development, dataset/semantic model design, DAX proficiency.
• SQL Server / Azure SQL / Postgres: query optimization, schema design, stored procedures.
• Azure DevOps: Git-based development workflows, CI/CD for data pipelines.

Responsibilities

• Design and implement dimensional models, star and snowflake schemas with rigor.
• Build and maintain semantic models that serve as the single source of truth for reporting.
• Implement SCD strategies appropriate to each domain.
• Own master data engineering with golden records and cross-system identity resolution.
• Establish and enforce data modeling standards across the team.
• Design and operate real-time pipelines using streaming technologies and determine when streaming is appropriate.
• Drive down data staleness through scheduling, incremental loads, and orchestration design.
• Tune performance across the stack including partitioning, indexing, and Direct Lake readiness.
• Apply operational discipline: observability, alerting, SLAs, failure recovery, capacity planning.
• Design controls for sensitive data (financials, PII, HIPAA).
• ETL/ELT: robust, scalable pipelines with CDC, batch and streaming architectures.
• Ensure idempotent, recoverable pipelines and be the senior technical voice in code review.
• Translate requirements into semantic models and provide trusted data surfaces for BI and AI/ML.
• Define data contracts and own platform developer experience: documentation and onboarding.

Tools

Microsoft Fabric

Power BI

SQL Server / Azure SQL / Postgres

Azure DevOps

Confluent Cloud / Kafka

Job description

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.

Pay Range: $180 - 200k USD

Job Summary

The 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 rigor
• Build and maintain semantic models that serve as the single source of truth for business reporting
• Implement Slowly Changing Dimension (SCD) strategies appropriate to each domain
• Own master data engineering: golden record patterns, source-of-record authority, cross-system identity resolution
• Establish and enforce data modeling standards across the team
• Design 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't
• Relentlessly drive down data staleness in non-streaming scenarios through intelligent scheduling, incremental load optimization, and pipeline orchestration design
• Own performance tuning across the full stack - query optimization, partition strategy, indexing, Delta table compaction, semantic model refresh efficiency, and Direct Lake readiness
• Apply operational engineering discipline: pipeline observability, alerting, SLA definition, failure recovery, and capacity planning
• Design and implement controls appropriate for sensitive data (financials, PII, HIPAA, etc.)

ETL / ELT Pipeline Development

• Build robust, scalable, observable pipelines - watermark-based incremental loads, CDC patterns, batch and streaming architectures
• Ensure pipelines are idempotent, recoverable, and production-hardened
• Serve as the senior technical voice in code review - your approval carries weight

Report & Analytics Delivery

• Translate business requirements into semantic models and report-layer artifacts that non-technical users can trust and navigate
• Serve 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 Lake
• Define and enforce data contracts - schema stability, access patterns, SLAs - for each consumer class
• Own the developer experience of the platform: discoverability, documentation, and onboarding

Required

• Microsoft Fabric: Lakehouses, Notebooks, Dataflows Gen2, Event streams, Semantic Models, Direct Lake mode
• Power BI: report development, dataset/semantic model design, DAX proficiency
• SQL Server / Azure SQL/Postgres: query optimization, schema design, stored procedures
• Azure 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 risk

Preferred Qualifications

• Familiarity with broader Azure Data Services (Azure Data Factory, Synapse Analytics, ADLS Gen2, Event Hubs) as complementary tooling
• Experience in a private equity-backed or multi-entity portfolio company environment
• Exposure to MDM platforms (Profisee, Semarchy, Ataccama, or equivalent)
• Experience with Confluent Cloud / Apache Kafka for streaming ingestion into Fabric or Synapse
• Familiarity with cross-tenant Azure / Fabric architecture
• Background in business analysis, solutions architecture, or pre-sales engineering
• Microsoft Fabric or Azure Data Engineer certifications

• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k)
• Life Insurance (Basic, Voluntary & AD&D)
• Paid Time Off
• Short Term & Long-Term Disability
• Training & Development
• Wellness Resources