About The Company

TalentBridge is a leading organization committed to delivering innovative data solutions that empower businesses to make data-driven decisions. With a focus on leveraging cutting-edge technologies and fostering a collaborative environment, TalentBridge strives to provide exceptional services in data management, analytics, and digital transformation. Our team of experts works closely with clients across various industries to understand their unique challenges and deliver tailored solutions that drive growth and efficiency.

About The Role

We are seeking a highly skilled Data Engineer to join our dynamic team on a contract-to-hire basis. This role offers an exciting opportunity to work on complex data systems, transforming raw data into actionable insights that support strategic decision-making. The successful candidate will be responsible for designing, building, and maintaining scalable data pipelines, storage solutions, and analytical models.

This position is critical in ensuring the integrity, security, and accessibility of data assets across the organization. The initial contract duration is six months, after which there is potential for full-time employment based on performance and project needs. The start date is immediate, with an anticipated commencement on September 14th.

Qualifications To excel in this role, candidates should possess a strong foundation in data engineering, with expertise in cloud-based data platforms and big data technologies. Proficiency in Python and SQL is essential, along with experience in building and optimizing large-scale data pipelines. Familiarity with Apache Spark, PySpark, and distributed data processing frameworks is required.

Hands-on experience with Microsoft Azure services, including Azure Data Factory, Azure SQL Database, and Microsoft Fabric, is highly desirable. Candidates should also have a solid understanding of data modeling, data warehousing, and analytics tools such as Power BI, SSAS, and DAX.



Excellent problem-solving skills, attention to detail, and the ability to work collaboratively in a fast-paced environment are crucial.

Responsibilities

Data Architecture and Design

- Design scalable, reliable, and secure data solutions that meet real business needs.
- Develop data models, data flows, and integration architectures from the ground up.
- Own the full lifecycle of data solutions — from requirements gathering to deployment in production environments.
- Ensure solutions align with best practices and business requirements.

Data Ingestion And Integration

- Build and manage data pipelines to ingest data from various sources, including third-party systems and RESTful APIs.
- Create ETL/ELT processes using Azure Data Factory, Fabric Data Flows, and Notebooks.
- Embed Master Data Management (MDM) solutions into pipelines, ensuring seamless data synchronization across platforms.

Data Storage And Management

- Design and implement data storage solutions utilizing Microsoft Fabric, Azure SQL Database, and Azure Delta Lake.
- Define match, merge, and survivorship rules for master data management, ensuring proper integration with other systems.

Data Transformation And Processing

- Utilize Python, PySpark, and Fabric Notebooks for large-scale data processing and transformation.
- Implement transformation logic to prepare data for analysis and reporting purposes.
- Optimize workflows for efficiency and scalability to handle growing data volumes.

Analytics And Reporting

- Design and develop SSAS OLAP cubes, tabular,



and semantic models to support complex analytical queries.
- Define dimensions, hierarchies, and measures; write MDX and DAX queries for data retrieval and manipulation.
- Integrate models with reporting tools such as Power BI and Excel to deliver dashboards and insights.

Data Quality

- Implement data quality checks, validation processes, and monitoring to ensure data accuracy and consistency.
- Maintain compliance with data governance policies throughout the data lifecycle.

Monitoring And Optimization

- Monitor data solutions for performance, reliability, and scalability; troubleshoot issues promptly.
- Optimize query performance through indexing, partitioning, and other best practices.

Security

- Implement role-based access controls, auditing, and encryption to safeguard data assets.

Documentation And Training

- Document data architectures, processes, and procedures for future reference.
- Provide training and support to team members and end-users to maximize data platform utilization.

Benefits Joining TalentBridge offers a range of benefits including exposure to innovative projects, opportunities for skilled growth, and the chance to work with a talented team of experts. We provide a competitive compensation package, flexible work arrangements, and access to continuous learning resources. Our environment fosters collaboration, creativity, and the pursuit of excellence. As part of our team, you will have the opportunity to contribute to impactful projects that shape the future of data-driven decision-making in diverse industries.

Equal Opportunity

TalentBridge is committed to fostering an inclusive and diverse workplace. We are an equal opportunity employer and do not discriminate based on race, color, religion, gender, sexual orientation, gender identity, age, disability, or any other protected characteristic. We believe that diversity enhances our ability to

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