ETL Data Engineer

ETL Data Engineer - DIRECT HIRE FULL TIME

The Data Engineer will be responsible for establishing our enterprise data strategy, building foundational infrastructure, and creating the roadmap for a scalable data organization. This role blends technical excellence with business impact, focusing on solutions that improve decision-making and operational efficiency.

With direct support from the IT Director and CFO, the first 3 6 months will be spent building robust data pipelines, integrating key systems (ERP, CRM, manufacturing), and establishing technical and governance standards. You will then progressively deliver high-value analytics initiatives that demonstrate tangible business impact.

This role requires an architect s vision, an engineer s skillset, and a builder s mindset someone comfortable making foundational technology choices, implementing proven best practices, and scaling a data function from zero to maturity.

Essential Duties and Responsibilities

Data Architecture & Infrastructure

• Design and implement foundational data architecture that will scale with the organization.
• Establish technical standards, naming conventions, and governance processes for all data assets.
• Select and implement a modern data stack (cloud platform, storage, integration tools, orchestration) aligned with long-term goals platform selection will be determined by this role based on Dunmore's specific needs and requirements.

Pipeline Development & Integration

• Build ETL/ELT pipelines integrating legacy ERP, Salesforce, manufacturing execution systems, and the Microsoft 365 ecosystem.
• Create data ingestion and transformation processes that ensure data is clean, validated, and business-ready.
• Automate repetitive processes, replacing manual data manipulation with scalable engineering solutions.

Data Enablement & Analytics

• Partner with business stakeholders to translate requirements into data solutions that drive measurable value.
• Develop data models that support enterprise reporting and analytics.
• Enable Power BI as the core analytics platform, delivering curated datasets for self-service reporting.

Governance, Quality, & Security

• Implement data governance practices including metadata management, lineage tracking, and access controls.
• Ensure data quality through monitoring, reconciliation, and exception handling processes.
• Define security best practices including encryption, role-based access, and compliance with relevant regulations.

Leadership & Scaling

• Act as technical owner of data architecture decisions.
• Manage and coordinate with third-party consultants for specialized implementations.
• Lead the recruitment and onboarding of additional data team members as the function scales.
• Mentor colleagues and enable self-service capabilities without creating technical debt.

Qualifications

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Knowledge, Skill, and Abilities:

• Programming & Query Languages: Proficiency in SQL and Python for data engineering tasks.
• Data Modeling: Strong knowledge of dimensional modeling, star/snowflake schema design, and performance tuning.
• Integration & Orchestration: Experience with ETL/ELT frameworks (e.g., Azure Data Factory, dbt, Apache Airflow).
• Cloud Platforms: Hands-on experience with modern cloud data platforms (e.g., Microsoft Fabric, Azure, AWS, Databricks). Ability to evaluate and select the optimal platform for enterprise needs.
• Data Storage: Familiarity with relational databases (SQL Server, PostgreSQL) and file-based storage (Parquet, CSV, Delta).
• BI & Visualization: Experience preparing data for Power BI and enabling enterprise reporting.
• Security & Compliance: Knowledge of data governance, RBAC, encryption, and compliance standards (GDPR, ITAR, CMMC).
• APIs & Streaming: Understanding of REST API integrations and streaming technologies (Kafka, Event Hubs).
• DevOps & CI/CD: Version control with Git, automated testing, and deployment of data pipelines.
• Values Alignment: Strong intellectual curiosity about how data can transform decision-making.
• Business Impact Focus: Balances technical rigor with delivering measurable outcomes.
• Engineering Excellence: Solid software engineering background applied to data solutions.
• Best Practices Mindset: Implements proven architectural patterns and avoids unnecessary reinvention.
• Collaboration Skills: Able to partner effectively with technical and non-technical teams.
• Leadership Potential: Capable of defining team culture and technical standards for a growing data function.

Education and Experience

• Bachelor s degree in Computer Science, Software Engineering, Information Technology, related technical field, or equivalent practical experience.
• Minimum 2 years of hands-on experience building production data infrastructure and pipelines.
• Demonstrated experience building significant data infrastructure or platforms from inception.
• Background in data engineering or software engineering with a data focus.
• Experience integrating multiple enterprise systems (ERP, CRM, manufacturing systems preferred).
• Experience with cloud platforms and modern data stack tools.
• Familiarity with Microsoft 365 integration in enterprise environments.
• Manufacturing or industrial sector experience preferred.

Cloud certifications (Azure, AWS, Databricks) are a plus.