Data Engineering Lead
About The Position
Dorman Products is seeking a Data Engineering Lead to architect, modernize, and scale our enterprise data platform. This role blends hands-on engineering with leadership, requiring deep expertise in dimensional modeling, data architecture, and ETL development, along with experience across modern cloud data platforms. The ideal candidate will bring strong SAP HANA experience to support current systems while driving the transition toward a cloud-first architecture leveraging Microsoft Fabric, Azure Data Services, Databricks, and Python-based data engineering frameworks. This leader will play a key role in enabling advanced analytics and AI-driven capabilities across the organization. This is a hybrid role in our corporate headquarters in suburban Philadelphia (Colmar, PA) with the expectation to be onsite two days per week.
Requirements
- Strong experience in dimensional modeling and data architecture (MUST HAVE)
- Expertise in ETL/ELT frameworks and pipeline orchestration
- Hands-on experience with modern data platforms: Microsoft Azure (Fabric, Data Lake, Synapse), Databricks / Delta Lake, Python for data engineering
- Experience with medallion/lakehouse architecture patterns
- Hands-on experience with SAP HANA modeling and performance tuning (MUST HAVE)
- Understanding of SAP ECC/S4 data structures and integration patterns
- Experience enabling reporting solutions (Power BI preferred, plus SAP BO/Qlik familiarity helpful)
- Strong understanding of how data models support analytics and reporting workloads
- GitHub or equivalent for version control
- CI/CD and DevOps practices for data pipelines
- Familiarity with data governance, lineage, and cataloging tools
- Bachelor’s degree in Computer Science, Information Systems, or related field
- 5+ years in data engineering / data architecture
- 3+ years in leadership or senior technical role
Nice To Haves
- SAP BO/Qlik familiarity helpful
Responsibilities
- Design and implement scalable enterprise data architectures using dimensional modeling (Kimball/star schema) and modern lakehouse patterns
- Develop and maintain conceptual, logical, and physical data models aligned to enterprise analytics needs
- Define and enforce data modeling standards, governance, and best practices
- Design architectures aligned with Medallion (Bronze/Silver/Gold) data layering
- Ensure models support both traditional BI and emerging AI/ML use cases
- Architect and oversee development of scalable ETL/ELT pipelines using modern tooling (Databricks, Azure Data Factory, Fabric pipelines, Python)
- Optimize ingestion patterns from SAP (ECC/HANA) and other source systems into cloud platforms
- Partner with developers to ensure reliability, scalability, and observability of pipelines
- Support both batch and near real-time data ingestion frameworks
- Leverage SAP HANA expertise to support existing data models, views, and integrations
- Optimize SAP HANA (Calculation Views, CDS) for performance and data extraction
- Guide integration strategies from SAP ECC/S4 into modern cloud data platforms
- Support SLT or CDC-based replication strategies
- Drive adoption and optimization of Microsoft Azure ecosystem (Fabric, Data Lake, Synapse, Databricks)
- Design and implement lakehouse architectures using Delta Lake principles
- Promote use of Python and modern data engineering frameworks
- Lead platform modernization initiatives and tool evaluations
- Define and enforce data quality frameworks, lineage, and metadata management
- Ensure observability, monitoring, and performance tuning across pipelines and warehouses
- Align with enterprise data governance standards
- Lead, mentor, and grow a team of data engineers and BI/reporting developers
- Establish engineering best practices including CI/CD, code reviews, and version control (GitHub)
- Drive roadmap for modern data platform transformation and AI readiness
- Foster innovation and continuous improvement mindset within the team
- Translate business requirements into scalable data solutions
- Partner with BI, analytics, and data science teams to enable self-service analytics and AI use cases
- Communicate technical strategy effectively to leadership and business stakeholders
Benefits
- medical
- dental
- vision
- basic life insurance
- paid time off (sick/vacation)
- Paid Parental Leave
- paid holidays
- floating holidays
- 401k retirement plan (with company match and profit-sharing)
- Discounted Employee Stock Purchase Plan
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What This Job Offers
Job Type
Full-time
Career Level
Senior
