Senior Application Data Architect
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Job Description
Senior Application Data Architect leading enterprise data architecture and engineering initiatives. Collaborating with cross-functional teams to design and build scalable data solutions.
Responsibilities:
- Design and evolve enterprise data architectures, including Lakehouse, Data Warehouse, pipelines, semantic models, and reporting layers.
- Define and maintain architectural standards, patterns, and best practices across Microsoft Fabric and Azure services.
- Translate enterprise data strategy into epics, features, and actionable technical stories.
- Lead technical planning activities, identifying dependencies, risks, and trade-offs early in the lifecycle.
- Establish and enforce standards for data quality, taxonomy, pipeline design, and semantic modeling.
- Review solution designs and critical implementations to ensure scalability, performance, and maintainability.
- Act as a technical leader and mentor, elevating engineering practices and system-level thinking.
- Design, build, and enhance data pipelines, dataflows, notebooks, and semantic models.
- Contribute hands-on to complex and high-impact initiatives where architecture and implementation intersect.
- Support platform modernization, including migration from on-prem SQL Server to Microsoft Fabric.
- Optimize data solutions for performance, reliability, and cost efficiency.
- Collaborate with Data Scientists to productionize ML models and integrate them into enterprise pipelines.
- Apply AI-assisted techniques to improve development workflows and solution quality.
- Deliver scalable, maintainable, and high-quality data solutions aligned with best practices.
- Participate in cross-project planning and release activities.
- Collaborate with Product Owners and stakeholders to align solutions with business needs and priorities.
- Monitor systems using logs and dashboards to ensure performance, reliability, and issue resolution.
- Create and maintain clear, concise technical documentation (architecture, systems, processes).
Requirements:
- 4+ years of experience in software/data engineering (Python, PySpark, Spark or similar)
- Strong experience designing and building enterprise data platforms (Lakehouse, Data Warehouse, Analytics)
- SQL, relational databases, and large-scale data systems
- Data pipelines, ETL/ELT processes, and query optimization
- Semantic modeling and reporting tools (e.g., Power BI)
- Experience with cloud data platforms (preferably Azure / Microsoft Fabric or similar)
- Familiarity with distributed data technologies (e.g., Spark, Kafka, Hadoop or cloud-native equivalents)
- Understanding of CI/CD, DataOps/MLOps, and modern deployment practices
- Experience working with APIs and system integrations.
- Bachelor’s degree in Computer Science or related field (or equivalent experience)
Benefits:
- Health insurance
- 401(k)
- Flexible work arrangements
- Professional development
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