Join our team as a Senior Full Stack Engineer, contributing to the Identity Data Management project. This role is pivotal in refining and maintaining our core Identity Management System, which is crucial for managing user identities across all enterprise systems.

We are seeking a Data Engineering Consultant to enhance and uphold our existing Identity Management System. This system is the backbone for managing user identities across various enterprise platforms.

You will lead the design, development, and ongoing maintenance of enterprise-scale identity management platforms. This involves creating robust IDM data integration and API solutions.

Key duties include establishing data validation, cleansing, reconciliation, and governance frameworks to ensure the accuracy and integrity of identity data. You will also architect and optimize data models, data lakes, and warehouse structures to support identity analytics, access reviews, compliance reporting, and audit needs.

Furthermore, you will implement solutions using Azure Data Factory, Databricks, SQL, Spark, or similar cloud data platforms. A significant part of the role involves optimizing ETL/ELT processes, automating data workflows, and enhancing pipeline reliability, scalability, and monitoring. Ensuring that data engineering solutions meet stringent security standards, privacy regulations, audit requirements, and enterprise IAM policies is paramount.

Collaboration is key; you will work closely with IDM architects, security specialists, application owners, and business stakeholders to gather data requirements and deliver effective enterprise identity data solutions.

A minimum of 5.5 years of experience in Data Engineering is essential.

You should possess strong expertise in cloud-native application development, distributed systems, API design, database management, and contemporary DevOps methodologies.

Practical experience with PySpark, Python, SQL, and API development is a must.

Hands-on proficiency with Azure Data Factory, Databricks, or comparable cloud platforms is required.

Crucially, you must have direct experience with Generative AI technologies, including OpenAI, Claude, Gemini, LangChain, Agents, RAG, Vector Databases, Prompt Engineering, and fine-tuning.

Experience in data governance, data quality assurance, and metadata management frameworks is also necessary.

While not mandatory, excellent communication and teamwork skills, a keen eye for detail, strong organizational abilities, and an analytical mindset are highly valued.