Data Engineer

Our client is a leading professional services firm specializing in data-first strategies for today's dynamic digital landscape.

Their innovative solutions, rooted in deep partnerships with major cloud providers and modern data platforms such as Databricks and Microsoft Fabric, streamline data delivery, unlock innovation, and build high-performing teams.

Our client empowers organizations to create stronger connections with external partners and customers by emphasizing speed to market, quality, and automation, ensuring success in a data-driven world.

Job Summary: We seek a proficient Data Engineer with expertise in Microsoft Azure, AWS, and Databricks technologies to build robust data pipelines that support scalable data solutions under the strategic guidance of our Data Architects.

What You'll Do:

1. Collaborate with business stakeholders and Data Architects to gather and refine data requirements for various projects.
2. Design and construct data pipelines using Databricks and Azure-based technical solutions, leveraging the latest in cloud technology toolsets.
3. Execute data pipeline projects under the architectural guidance and oversight of senior Data Architects.
4. Implement and maintain scalable data platforms and pipelines that ensure data integrity and support advanced data analytics.
5. Develop and maintain data models, reports, dashboards, and other data visualizations to meet business needs.
6. Ensure high data quality and continuous improvement of data processing and storage mechanisms.
7. Create detailed documentation for data pipeline designs, data models, and other project-related artifacts.
8. Continuously advance your technical expertise across a range of data technologies and cloud platforms.

Qualifications:
1. 2+ years of hands-on experience building data solutions on cloud platforms, particularly with Databricks and Microsoft Azure Data Platform.
2. Proficient with on or more of the top industry ETL tools – Lakeflow, Azure Data Factory, Glue, Fivetran, Airflow, etc.
3. Demonstrated ability in developing and implementing practical solutions for data migration from on-premise environments to Azure, AWS, or GCP.
4. Familiarity with data visualization and reporting tools like Power BI, Databricks, Tableau, etc..
5. Strong skills in data modeling for cloud data warehouses and developing data pipelines.
6. Proven track record in full life-cycle data warehouse implementations and data integrations.
7. Solid understanding of data architecture and data integration processes.
8. Experience with data modeling applications such as Visio, ER/Studio, ER/Win, or similar.
9. Expert knowledge in managing data services with Azure Data Lake, Azure Storage, Azure Synapse, and Azure SQL database.
10. Ability to quickly learn and apply new technologies in a fast-paced environment.
11. Strong communication skills, capable of effectively articulating data-driven insights and technical concepts to a diverse audience.