System Data Engineer,
Pasadena, CA (Hybrid),
Only Local to CA.
Role Overview
We are looking for a highly skilled Senior Data Engineer / Data Architect who can evaluate the existing enterprise data lake architecture, lead architecture improvement recommendations, and establish scalable data governance processes and controls. The successful candidate will be responsible for designing and modernizing data pipelines, strengthening data quality and security controls, supporting Microsoft Fabric, Azure Synapse, Power BI, Power Automate, Microsoft Purview, and related Azure data services, and mentoring the data management team. Optional knowledge of Snowflake is preferred as an additional capability to support future-state cloud data warehousing, lakehouse interoperability, workload evaluation, secure data sharing, performance optimization, and cross-platform architecture planning. The ideal candidate will combine hands-on engineering depth with architecture leadership, governance discipline, strong communication skills, and the ability to guide cross-functional teams through complex data platform decisions.
Responsibilities:
- The Senior Data Engineer / Data Architect will play a lead role in assessing, strengthening, and sustaining the enterprise data lake and reporting platform. This role combines solution architecture, data engineering, governance design, technical leadership, and operational support. Key responsibilities include:
- Assessing the current data lake architecture, including Raw, Curated, and Serving zones, ingestion patterns, transformation layers, security boundaries, lineage, and operational support model.
- Leading architecture recommendations and roadmap proposals for Azure Synapse, Microsoft Fabric, ADLS Gen2 / OneLake alignment, Power BI semantic models, CI/CD, monitoring, and scalable data platform modernization.
- Providing optional advisory support for Snowflake-related architecture considerations, including separation of storage and compute, virtual warehouse sizing, workload isolation, role-based access control, masking policies, secure data sharing, Snowpipe, Streams, Tasks, Time Travel, query performance tuning, resource monitoring, and cost optimization where Snowflake may be used or evaluated.
- Designing, developing, and maintaining reliable data pipelines and data integration patterns from authoritative source systems into governed data lake zones and certified reporting datasets.
- Establishing data governance processes and controls, including data cataloging, metadata standards, business glossary alignment, lineage, sensitivity labeling, data quality thresholds, access governance, and audit evidence retention.
- Partnering with business owners, data stewards, security, infrastructure, application teams, and governance stakeholders to translate business needs into secure, auditable, and supportable data solutions.
- Ensuring data quality, integrity, privacy, regulatory compliance, least-privilege access, separation of duties, and secure handling of sensitive data across the data platform.
- Defining operational standards for pipeline monitoring, alerting, incident triage, reconciliation, performance tuning, release validation, rollback planning, and production support readiness.
- Providing technical leadership, knowledge transfer, architecture guidance, code and design reviews, and mentoring for data engineers, BI developers, analysts, and data management team members.
- Creating architecture documentation, standards, design decision records, governance procedures, runbooks, and executive-ready recommendations for major data platform changes.
Requirements:
- Bachelor's degree in Computer Science, Information Technology, or a related field.
- Minimum of 7 years of experience in data engineering, data architecture, business intelligence platform engineering, or enterprise data platform delivery is required.
- Strong proficiency with Azure Synapse, Microsoft Fabric, ADLS Gen2 / OneLake concepts, Power BI, Power Automate, Microsoft Purview, and Azure data integration patterns is required.
- Optional working knowledge of Snowflake architecture and administration concepts is preferred, including the storage, compute, and cloud services layers; virtual warehouses; micro-partitioning and clustering; role-based access control; masking policies; secure data sharing; Snowpipe; Streams; Tasks; Time Travel; resource monitors; and platform cost controls.
- Strong knowledge of data lake architecture, lakehouse patterns, data warehousing, dimensional modeling, semantic modeling, metadata management, and enterprise data governance best practices is required.
- Experience leading architecture assessments, proposing target-state architecture changes, documenting technical roadmaps, and presenting recommendations to technical and non-technical stakeholders is required.
- Advanced SQL skills and experience with ETL/ELT development, pipeline orchestration, data modeling, performance tuning, data reconciliation, and troubleshooting complex data issues is required.
- Demonstrated experience implementing governance controls such as role-based access, sensitivity classification, lineage, cataloging, data quality rules, audit logging, change control, and production release evidence is required.
- Ability to mentor technical staff, establish engineering standards, lead design reviews, and promote consistent development, documentation, and support practices across the data management team is required.
- Excellent verbal and written communication skills, including the ability to explain architecture decisions, governance controls, risks, tradeoffs, and implementation plans to executives, business stakeholders, and technical teams, are required.
- Experience with DevOps practices for data platforms, including Git-based source control, pull request reviews, CI/CD pipelines, deployment automation, environment promotion, rollback planning, and separation of duties is preferred.
- Experience comparing Snowflake with Microsoft Fabric, Azure Synapse, ADLS Gen2, OneLake, or other enterprise data platforms for workload fit, governance alignment, interoperability, scalability, performance, security, cost management, and long-term architecture planning is preferred.
- Knowledge of data privacy, security, regulatory compliance, and audit-ready control frameworks for sensitive enterprise data is preferred.
Preferred Certifications:
- The following certifications are preferred and may be considered evidence of relevant technical depth, architecture capability, governance awareness, and commitment to continuous professional development:
- Microsoft Certified: Fabric Data Engineer Associate or Microsoft Certified: Fabric Analytics Engineer Associate.
- Microsoft Certified: Azure Solutions Architect Expert or comparable cloud architecture certification demonstrating experience designing secure, scalable, and governed enterprise solutions.
- Microsoft Certified: Power BI Data Analyst Associate or equivalent certification demonstrating data modeling, semantic model design, dashboard development, and analytics delivery skills.
- Microsoft Purview, information protection, data governance, privacy, security, or compliance-related certification demonstrating familiarity with cataloging, classification, lineage, retention, access governance, and audit controls.
- Azure fundamentals, data fundamentals, security fundamentals, or equivalent cloud platform certification is preferred when combined with demonstrated hands-on enterprise data platform experience.
- Snowflake SnowPro Core, SnowPro Advanced Data Engineer, SnowPro Advanced Architect, or equivalent Snowflake certification is preferred as supplemental evidence of cloud data warehousing, platform optimization, governance, security, and cross-platform data engineering knowledge.
Eligibility Criteria
- Must be legally authorized to work in the country USA.
- Proven track record of leading successful data engineering, data architecture, data lake modernization, or enterprise reporting platform initiatives.
- Demonstrated ability to evaluate existing architectures, identify gaps, recommend practical improvements, and guide teams through implementation.
- Strong commitment to data accuracy, governance discipline, documentation quality, production stability, and audit readiness.
- Ability to manage competing priorities across architecture planning, hands-on engineering, stakeholder engagement, production support, and team mentorship.
Strong capacity for continuous learning and professional development, including staying current with Microsoft Fabric, Azure Synapse, Purview, Power BI, cloud data governance, data security, Snowflake capabilities, and modern data architecture practices
