Data Architect (вакансія неактивна)

Tech stack: Azure Data Factory, PowerBI, Excel, PowerApps, Azure Fabric, Azure Purview, Palantir Foundry AIP, Salesforce, SAP ECC, OSCRE, Spark, SQL, Python, Typescript

About the role

Our Client is a leading partner for global investment in real assets, with over €58bn of assets under management. They offer their institutional and private clients various attractive investment opportunities delivering long-term sustainable growth.

This client engagement is a multi-phase engagement to modernize the client’s data practices, starting with the deployment of a modern deployment platform which will be used to consolidate data from existing silos and in the process gain the customer operational savings, accuracy and speed.

The COTS data platform has not been selected yet, and in this role, the data engineer will work closely with the lead platform architect on the project to deliver the following:

1. A reasoned recommendation for a data platform that is the “best fit” for the client. This recommendation will be in the form of a detailed memorandum covering the differences in platforms, as well as development and operating cost models for each of the choices.
2. Two sample data platform integrations will be used to aid the client in making the final decision regarding the best data platform for their needs. This will involve implementing data ingestion, cleansing, report and dashboard authoring, data quality controls, issue tracking, and CI/CD for each platform, while keeping accurate track of effort required so that effort data can be used in planning Phase 2 of this project.

Additionally, the Data Engineer will participate in select discovery activities with the Proxet team and the client for three use cases that will become the foundation of Phase 2 activities. This role is expected to continue through Phase 2 and beyond, and will likely include travel to and from the client site in the EU..
Location
Remote EU

Skills & Experience

• Good knowledge and participation in the delivery on a modern data platform (Databricks, Snowflake, Azure Fabric, or equivalent)
• Strong Relational DB Skills, especially DQL
• Solid understanding of Data Warehousing concepts, include ETL/ELT, Governance, CDC, Orchestration, Ingestion, etc.
• Familiarity with data modeling and master data management
• Demonstrated track record of learning new technologies
• Commercial experience with Spark/PySpark
• storage formats: Parquet, Delta Lake;
• custom data applications, scraping, ingestion using Python
• Implementing CI/CD for data-centric projects
• Comfortable working with at least one cloud provider (Azure preferred)
• Preferred: Data Factory, Data Lake, SQL server, Azure Synapse, Power BI
• Fluent English