What are the responsibilities and job description for the Sr. Data Engineer position at SNNS, LLC?
Core Responsibilities
- End-to-end ownership of data pipelines, models, and analytics architecture — from design through production support
- Acts as the technical decision-maker for data platform standards and patterns
- Comfortable operating in environments with evolving requirements and incomplete data
- Ability to translate available data from pipelines into value-added analytics to the business’s benefit
- Expected to proactively identify business solutions, data gaps, quality issues, and architectural improvements
- Design and implement the Microsoft Fabric Lakehouse and data warehouse, and lead the transition from on-premises SQL-based solutions
- Develop and maintain ETL and ELT pipelines using Fabric Data Factory, SQL, and notebooks
- Ability to define and establish the semantic layer to enable servicing data to business resources for self service visualizations
- Apply scripting or notebook-based approaches, including Python/R/etc. where appropriate, for data transformation, automation, and data quality enforcement
- Integrate data from AS400 ERP, Salesforce, HubSpot, and other SaaS platforms
- Design analytical data models, fact and dimension tables, and curated data marts
- Implement CI/CD practices for data pipelines and analytics assets, enabling agile, reliable, and controlled production deployments
- Operate in an Agile delivery environment
- Optimize platform performance, scalability, reliability, and cost
- Support and stabilize existing datasets and dashboards
- Drive Power BI adoption and define migration approach for legacy tools and standards
- Design and implement data quality checks, monitoring, alerting, recovery mechanisms, and governance controls
- Maintain documentation for pipelines, models, and integration patterns
- Partner with IT and business stakeholders to translate requirements into data solutions
- Bachelor’s degree in Computer Science, Information Systems, or equivalent experience
- 5 years of experience in data engineering, including enterprise data warehouse and analytics platforms
- Advanced SQL skills with strong analytical and enterprise data modeling experience
- Experience designing and operating data warehouses, lakes, or Lakehouse architectures in a cloud environment
- Experience integrating ERP systems, CRM, and SaaS data sources
- Experience supporting BI tools, including Tableau (phasing out) and Power BI
- Strong communication skills with technical and business teams
- Azure Synapse, Data Factory, or Databricks
- Salesforce and HubSpot data models and APIs
- Data governance, quality frameworks, and access controls