Financial Data Engineer Intern assisting with model integration and process automation at Transamerica. Focused on data engineering tasks with collaboration across IT and Finance teams.
About the role
- Data Engineer managing reliable data pipelines and solutions using Microsoft Azure and Python. Collaborating across teams to meet business data needs in a scalable environment.
Responsibilities
- Data Engineering & Development
- Design, build, and maintain reliable, scalable data pipelines using batch and incremental processing patterns.
- Develop and optimise SQL-based transformations and data models for analytics and reporting use cases.
- Write clean, efficient and testable code using Python (Pandas / PySpark).
- Implement and support data warehouse and lakehouse solutions following best practices (e.g., Bronze/Silver/Gold).
- Build curated datasets and semantic models to enable Power BI dashboards and reports.
- Cloud & Platform
- Work extensively on the Microsoft Azure data ecosystem, including:
- Azure Synapse Analytics
- Azure Databricks
- Azure Data Factory (ADF)
- Azure Data Lake (ADLS Gen2)
- Power BI
- Participate in design and implementation of solutions on Microsoft Fabric (nice to have).
- Support workloads running on or integrated with AWS and GCP where required.
- Operational Excellence
- Ensure data pipelines are robust, monitored, and production-ready.
- Troubleshoot and resolve data quality, performance, and reliability issues.
- Support production systems and participate in incident resolution and root-cause analysis.
- Apply FinOps principles to optimize cloud data platform costs.
- Collaboration & Leadership
- Act as a technical mentor for junior and mid-level data engineers.
- Review code and designs with a focus on quality, performance, and maintainability.
- Work closely with analysts, product owners, and stakeholders to understand real business requirements and translate them into data solutions.
- Contribute positively to team culture with a collaborative and ownership-driven mindset.
Requirements
- 6-9 years of experience in data engineering, analytics engineering, or software engineering.
- 5+ years of strong hands-on experience with:
- SQL (complex queries, performance tuning, data modeling)
- Data Warehousing concepts
- Data visualization using Power BI
- Strong programming experience with Python, especially Pandas (PySpark experience is a plus).
- Proven experience building and supporting data platforms on Microsoft Azure.
- Strong analytical skills and ability to represent data meaningfully by understanding business context.
- Good to Have
- Exposure to Microsoft Fabric.
- Basic working knowledge of:
- Bash / Shell scripting
- Networking fundamentals
- Infrastructure as Code (Terraform)
- IAM and security concepts
- Familiarity with data governance concepts such as data quality, lineage, and access control.
- What We Look For
- A strong hands-on senior engineer, not just a designer.
- Someone who takes ownership of data solutions end-to-end.
- A team player with good cultural adaptability and communication skills.
- Curiosity and passion for continuously improving data systems.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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