The Role
As a Data Engineer specializing in Alteryx and Dataiku, you will design, develop, and maintain ETL pipelines and data workflows using these platforms. The role requires expertise in SQL, Python, cloud technologies (Azure/AWS), and collaboration within Agile teams.
You are expected to study existing flows in Alteryx, reaffirm the complexity and migrate ( rewrite/ re develop in Dataiku) with an appropriate approach agreed with the customer
Your responsibilities:
•Develop and optimize automated data pipelines with Alteryx and Dataiku for data integration, transformation, and loading into data lakes or warehouses (e.g., Snowflake, BigQuery).
•Migrate and convert workflows between platforms, leveraging Python for efficiency and reliability.
•Implement data quality checks and governance processes to ensure operational reliability.
•Collaborate with analytics teams, data scientists, and business stakeholders to define requirements and provide production support.
•Manage cloud-native data systems and services in AWS or Azure.
•Document processes and solutions, working within Agile teams using tools like JIRA.
Essential skills/knowledge/experience
Hands-on experience with Alteryx Designer and Dataiku DSS; relevant certifications are desirable.
•Strong proficiency in SQL and Python for data manipulation and analytics.
•Experience with RDBMS and data querying tools.
•Familiarity with cloud platforms (AWS, Azure, GCP) and related data services.
•Troubleshooting and solution design for technical incidents.
•DevOps experience with GitLab CI/CD and PowerShell scripting.
•Effective communication with IT stakeholders and business partners.
•Development support for data science engineering and production teams.
•Design and implementation of data science platforms (Alteryx, Dataiku, Azure ML).
•Compliance with operational, risk, and change management guidelines.
•Strong analytical, reasoning, and communication skills.
Desirable skills/knowledge/experience: (As applicable)
•Experience with big data frameworks (e.g., PySpark).
•Domain knowledge in industries such as Insurance.
•Familiarity with BI tools (Qlik, Power BI).