Senior Data Engineer
Company Overview Based in Silicon Valley, Bridgepointe was founded in 2002 on the principle that businesses need a strategic partner and advocate when procuring, implementing, and maintaining IT services and infrastructure. The Company’s IT Strategists offer business leaders direct access to a large portfolio of vendor-agnostic solutions, employing a six-step model that starts with getting to know a client’s business, challenges, and goals and culminates in recommendations and support around supplier selection. Bridgepointe’s expert IT Strategists help clients achieve optimal IT results without costly consulting agreements.
Job Description
We are looking for a skilled Senior Data Engineer to help design, build, and scale our modern data platform in Microsoft Fabric. This is a hands-on, high-impact role focused on building reliable ingestion and transformation pipelines, integrating data from core business systems, and creating well-governed data assets that support reporting, analytics, and future AI use cases. You will combine strong platform engineering skills with practical data architecture, integration, and modeling expertise. The ideal candidate can move comfortably between pipelines, notebooks, SQL, APIs, and stakeholder conversations—turning business requirements into scalable, production-ready data solutions. What You’ll Own Fabric Platform Engineering: Design and build scalable data solutions in Microsoft Fabric across Lakehouse, Warehouse, Pipelines, Notebooks, and OneLake. Data Integration: Build and maintain reliable ingestion and integration patterns across SaaS platforms, operational systems, flat files, and APIs. Data Modeling: Design and optimize curated data models that support enterprise reporting, analytics, and downstream consumption. Data Quality & Governance: Implement data quality checks, monitoring, lineage, and governance standards to improve trust, reliability, and maintainability. Integration Engineering: Integrate data from systems such as Salesforce, finance platforms, and third-party applications using REST APIs, files, and other modern ingestion patterns. Operational Excellence: Establish production-ready engineering practices including documentation, observability, performance tuning, error handling, and supportable handoffs. Stakeholder Partnership: Partner with business and technical stakeholders to translate requirements into scalable data products and integration solutions. Required Technical Skills Microsoft Fabric: Strong hands-on experience with Lakehouse, Warehouse, Data Pipelines, Notebooks, and OneLake in production-oriented environments. CI/CD & DevOps: Experience with continuous integration and continuous deployment practices, including source control with Git and delivery workflows using Azure DevOps. Spark / PySpark: Strong proficiency building notebook-based transformations and scalable data processing workflows. SQL: Advanced SQL skills including complex transformations, performance tuning, and dimensional data design. Python: Strong scripting and engineering skills for data processing, automation, and integration workflows. Cloud Data Foundations: Experience with Azure-based data services and modern cloud data platform concepts relevant to Microsoft Fabric. Storage & Table Design: Strong understanding of Delta Lake, Parquet, partitioning, and incremental processing patterns. Data Modeling: Strong experience designing dimensional and analytical models for reporting and self-service consumption. Integration Patterns: Experience building robust integrations using REST APIs, file-based ingestion, JSON, and related data exchange patterns. Engineering Practices: Experience with version control, reusable code patterns, testing, documentation, and collaborative development workflows.
Preferred Qualifications
Microsoft Certifications: DP-600 (Fabric Analytics Engineer) or DP-700 (Fabric Data Engineer). Reporting: Experience with Power BI and building optimized semantic models. Business Domain Knowledge: Experience integrating data from CRM, finance, commissions, or other operational business systems. Legacy Tools: Prior experience with legacy ETL and workflow automation tools is beneficial for migration tasks. Experience & Education 5+ years of experience in data engineering, data platform engineering, or similar hands-on roles. Education: Bachelor’s degree in Computer Science, Data Science, or a related field (or equivalent professional experience).
Benefits
Company subsidized Medical, Dental, and Vision Care benefits HSA Plan Short-term and Long-term Disability Company-paid AD&D and Life Insurance Competitive Pay 401k plan Unlimited PTO Flexible and innovative work environment Bridgepointe Technologies, LLC is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. For more information, please send an email to [email protected], or visit https://www.bridgepointetechnologies.com/ to learn more about Bridgepointe.