Data Engineer (Azure Fabric / Databricks)

We are seeking three Data Engineers to join a large-scale greenfield data modernization initiative for a Financial Services client. The team is building an enterprise data platform from the ground up, integrating more than 30 operational source systems into a centralized Lakehouse architecture. The primary focus of this role will be developing data ingestion, transformation, and modeling solutions that support the creation of a modern data lakehouse and semantic data layer. The client has dedicated Business Analysts and architects responsible for requirements gathering, data design, and source-to-target mapping. Data Engineers will be responsible for implementing and validating those designs through scalable, production-quality data pipelines. This is an excellent opportunity to work on a long-term strategic initiative that will evolve over the next 12 months, culminating in a curated Gold Layer that supports enterprise analytics, KPI reporting, and future business intelligence initiatives. Responsibilities: - Develop and maintain data pipelines that integrate data from 30+ operational source systems. - Build and support a modern Lakehouse architecture using Microsoft Fabric and Azure technologies. - Implement source-to-target mappings for business entities, dimensions, and fact structures. - Develop ETL/ELT processes using Azure Data Factory (ADF). - Create scalable and maintainable data transformation processes using Python and SQL. - Support the development of semantic models and KPI-driven data structures. - Validate data quality and perform unit testing on all developed solutions. - Collaborate with architects, Business Analysts, and stakeholders to ensure successful delivery. - Troubleshoot and optimize data processing performance and reliability. - Follow established development standards and best practices. Required Qualifications: - 3–5 years of professional Data Engineering experience. - Strong experience with Azure-based data platforms. - Hands-on experience developing ETL/ELT pipelines using Azure Data Factory (ADF). - Strong Python programming skills. - Advanced SQL development skills. - Experience with data warehousing, dimensional modeling, and - Lakehouse concepts. - Experience integrating data from multiple enterprise source systems. - Strong understanding of data quality validation and unit testing practices. - Ability to work independently in a distributed team environment. Preferred Qualifications: - Experience with Microsoft Fabric is highly preferred. - Candidates with strong Databricks experience will also be considered, particularly those with experience building modern Lakehouse architectures, scalable data pipelines, and enterprise data platforms on Azure. - Experience building semantic models and business KPI frameworks. - Experience supporting enterprise analytics initiatives. - Power BI experience is a plus but is not required during the initial phase of the project. - Financial Services industry experience is preferred. Additional responsibilities include: - Conducting code reviews and ensuring adherence to development standards. - Providing technical leadership and mentoring to other Data Engineers. - Reviewing unit testing and data validation processes. - Ensuring overall delivery quality and technical consistency. - Collaborating with architects and project leadership on technical decisions and implementation approaches. Interview Process: Interview 1 – Technical Assessment (60 Minutes): Focus Areas: - Azure Data Engineering - Azure Data Factory - Python - SQL - Data Modeling - Fabric and/or Databricks - Data Lakehouse Architecture Interview 2 – Culture & Team Fit - Communication skills - Collaboration style - Problem-solving approach - Client engagement and ownership mindset