Data Engineer (Azure Fabric / Databricks) Location
Remote (Must be available during Central Time business hours) Duration
12+ Month Contract Industry
Financial Services Position Overview
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 lead 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.
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Requisitos
English Level
Advanced conversational English required Seniority Level
Senior Lead Level
Beneficios
Contratación de planta
Esquema 100% remoto
Prestaciones de ley y superiores
Seguro de vida
Vales de despensa
Sueldo según aptitudes y experiencia
