Alteryx

Key Responsibilities:

• Design, build, and maintain Alteryx workflows for data preparation, transformation, and integration.
• Develop and support ETL/data workflows to ingest, cleanse, validate, and enrich data from multiple sources.
• Translate business requirements into technical workflow designs and reusable components/macros.
• Implement data quality checks, reconciliation logic, and exception handling to ensure accuracy and completeness.
• Optimize workflow performance by improving logic, reducing run time, and managing resource usage effectively.
• Document workflow logic, data mappings, and operational steps to support maintainability and handovers.
• Collaborate with analysts, data engineers, and stakeholders to troubleshoot issues and deliver enhancements.
• Support production runs, monitor scheduled workflows, and resolve failures within defined timelines.

Minimum Qualifications:

• Bachelors degree (or equivalent) in Engineering/Technology/Computer Applications/Science (e.g., BTech, BE, BSc, MCA, MTech, MSc).
• 2-5years of experience working with Alteryx to build and maintain data preparation or automation workflows.
• Strong hands-on experience in ETL and data workflow development, including transformation and validation steps.
• Solid understanding of data concepts such as joins, aggregations, filtering, data types, and schema handling.
• Ability to analyze requirements, debug workflow issues, and deliver reliable outputs with attention to detail.

Preferred Qualifications:

• Experience integrating Alteryx workflows with databases and file-based sources, including efficient input/output patterns.
• Familiarity with SQL for data validation, reconciliation, and performance-aware querying alongside Alteryx pipelines.
• Exposure to workflow scheduling/automation and operational support for recurring data processes.
• Understanding of analytics lifecycle practices such as versioning, documentation standards, and reusable workflow design.
• Ability to communicate clearly with stakeholders, present findings, and recommend improvements to data processes.

Good to have skills:

SQL, Data Warehousing, Data Quality Frameworks, Power BI, Python