Director, Data Analytics

As a Data Analytics Engineer, you will play a crucial role in our data initiatives by designing, developing, and maintaining robust data pipelines. You will be responsible for extracting, transforming, and loading data from various sources, including the JLL Data Warehouses, into the Google Cloud environment.

As the business continues to grow, the Data Analytics Engineer role will help underpin the business transformation. It will support steering the technical ship from a data, insights, and reporting perspective. It will be heavily business facing and will be highly regarded internally.

We are looking for a Data Analytics Engineer working in the Business Intelligence area:

• With hands-on experience in Business Intelligence tools and databases
• Problem solver with strong analytical skills
• With experience in solutions delivery for both internal and external clients
• Experience in using visualization software like Tableau, Power BI, Google Looker Studio for development
• Experience with data modeling/transformation, ETL (Extract Transform Load) development (SQL)
• Experience with data storage solutions such as BigQuery, DataBricks, SQL Server
• Experience with data analytics in cloud platforms like GCP or Azure.

Responsibilities:

• Data Ingestion: Design and implement efficient data ingestion pipelines to extract data from JLL Data Warehouse and other sources. Leverage SQL, APIs, Azure/GCP functionalities, and other relevant tools to extract, transform, and load data for analysis.
• Data Transformation: Transform and clean data to ensure data quality and consistency.
• Data Loading: Load transformed data into Google Cloud Platform (GCP).
• Data Modeling: Develop data models to support reporting and analytics.
• Data Pipeline Optimization: Monitor and optimize data pipelines for performance and reliability.
• Collaboration: Work closely with data analysts, data scientists, and business stakeholders to understand their data needs.

Requirements:

• Technical Skills: Strong proficiency in SQL, Python, and GCP data services.
• Cloud Experience: Experience with cloud platforms, particularly GCP.
• Data Warehousing: Knowledge of data warehousing concepts and best practices.
• ETL/ELT: Experience with ETL/ELT processes and tools.
• Data Modeling: Ability to design and implement data models.
• Problem-Solving: Strong analytical and problem-solving skills.
• Communication Skills: Effective communication skills to collaborate with technical and non-technical stakeholders. Fluency in English is essential.