Data Domain Architect Lead- Operations Product
- Analyze and interpret complex data sets using Alteryx, Databricks, and Notebooks and deeply explore data to uncover trends, anomalies, and actionable insights for business operations.
- Develop and maintain Python scripts for data automation, transformation, and testing and design, implement, and manage automated scheduling solutions for data workflows (e.g., Airflow, Control M).
- Reverse engineer existing processes and workflows to improve efficiency and scalability and collaborate with end users to gather requirements and understand business needs.
- Develop and maintain comprehensive documentation for data models, ETL procedures, and data workflows.
- Build, test, and validate data pipelines, including developing test scenarios and assisting in UAT.
- Work closely with engineering and cross-functional teams for successful project implementation.
- Provide insights and recommendations based on data analysis to support business decision-making.
- Work autonomously to achieve objectives and meet deadlines & identify new opportunities for process improvements and automation.
- Advanced technical knowledge of data management, governance, data architecture, and big data platforms (AWS, Databricks, Snowflake).
- Strong experience in Python programming for data wrangling, automation, and testing. Proficiency in Alteryx for data preparation, blending, and analysis and experience designing, implementing, and optimizing ETL processes and data pipelines.
- Hands-on experience with scheduling tools (Airflow, Control M, or similar) with strong understanding of data modeling concepts, including operational and analytical data.
- Proven experience as a Data/Business Analyst, Data Engineer, or similar technical role and proficiency in SQL and relational databases with experience in reverse engineering processes and workflows and strong problem-solving skills and attention to detail.
- Excellent communication skills for conveying technical information to non-technical stakeholders and comfortable working directly with end users and cross-functional teams.
- Bachelor’s degree in computer science, Information Technology, Business Administration, or a related field
- Experience in large-scale data handling and analytics.
- Working experience with Agile methodologies and understanding of Scrum and Kanban boards.
- Exposure to visualization tools (Tableau, Qlik, Power BI, Looker).
- Cloud certification is a plus.
- Experience with documentation tools (Confluence, Jira).
- Exposure to additional automation and scheduling tools.
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