Data Architect

Job Summary We are seeking an experienced Data Architect / Alteryx Engineer to design, develop, and lead enterprise-scale data integration and analytics solutions. The ideal candidate will have deep expertise in PySpark and Apache NiFi for large-scale data processing, data movement, and ETL/ELT architecture. Experience with Alteryx is preferred for supporting self-service analytics and workflow automation initiatives. This role will partner with business stakeholders, data scientists, cloud engineers, and application teams to build scalable, reliable, and high-performance data platforms that support business-critical reporting, advanced analytics, and AI/ML initiatives. Key Responsibilities

• Lead the architecture, design, and implementation of enterprise data engineering solutions.
• Develop and optimize large-scale data processing pipelines using PySpark.
• Design and manage complex data ingestion, transformation, and orchestration workflows using Apache NiFi.
• Build scalable batch and real-time data integration frameworks.
• Define enterprise data architecture standards, governance, and best practices.
• Collaborate with business and technology teams to gather requirements and translate them into technical solutions.
• Optimize data pipelines for performance, scalability, reliability, and cost efficiency.
• Support Alteryx-based workflows for business reporting, data preparation, and analytics use cases.
• Mentor junior engineers and provide technical leadership across projects.
• Drive cloud modernization and data platform transformation initiatives.
• Ensure compliance with security, governance, and data quality standards.
• Participate in architecture reviews and strategic technology planning.

• 10+ years of experience in Data Engineering, ETL Development, or Data Architecture.
• 5+ years of hands-on experience with PySpark development and optimization.
• Strong experience implementing and managing Apache NiFi data flows and processors.
• Expertise in distributed data processing and big data ecosystems.
• Strong SQL and data modeling skills.
• Experience designing enterprise-scale ETL/ELT frameworks.
• Hands-on experience with Hadoop/Spark ecosystems.
• Experience with data warehousing concepts and modern lakehouse architectures.
• Strong understanding of data governance, metadata management, and data quality practices.
• Experience leading technical teams and mentoring developers.
• Excellent stakeholder management and communication skills.

Preferred Qualifications

• Experience with Alteryx Designer and Alteryx Server.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Knowledge of Databricks and Delta Lake.
• Experience with Kafka, Airflow, Informatica, or similar integration tools.
• Familiarity with CI/CD, DevOps, and Infrastructure as Code.
• Exposure to AI/ML data pipelines and analytics platforms.
• Banking, Financial Services, or Enterprise Data Platform experience is highly desirable.