What are the responsibilities and job description for the Data Engineer/Analyst position at Leeds Professional Resources?
Senior Data Analyst (Data Engineering & Analytics Platforms)
We are seeking an experienced Senior Data Analyst/Engineer who operates at the intersection of analytics and data engineering. This role goes beyond traditional reporting responsibilities and involves building and maintaining reliable data pipelines, supporting enterprise analytics platforms, and delivering trusted data products used by business leaders.
Key Responsibilities
Data Pipeline Development & Platform Support
- Design, build, and maintain scalable ETL/ELT pipelines that ingest data from multiple sources including databases, APIs, and flat files.
- Help evolve the organization’s data platform as pipelines transition to modern Azure-based architectures and Microsoft Fabric environments.
- Develop reliable data workflows with strong scheduling, monitoring, and recovery processes.
Data Modeling, Quality & Governance
- Identify and resolve data quality issues through validation checks, reconciliation logic, and monitoring processes.
- Design and maintain structured data models and curated datasets that enable consistent metrics and reporting.
Analytics & Reporting
- Develop and maintain interactive dashboards and reporting solutions using Power BI and other BI tools.
- Support both modern reporting solutions and operational reporting environments where required.
Required Qualifications
- 6 years of experience working across data analytics, data engineering, or BI development.
- Strong experience building and supporting ETL/ELT pipelines and production data workflows.
- 6 years of experience creating dashboards and analytics solutions using Power BI.
- Experience working with modern analytics platforms, including Microsoft Fabric or similar technologies.
- Experience implementing CI/CD practices for data pipelines, datasets, or analytics assets.
- Proficiency with SQL and at least one programming language used for data analysis or transformation (Python, R, DAX, etc.).
Technology Environment
- SQL Server and DB2
- SSIS and Azure Data Factory pipelines
- Power BI and SSRS reporting
- Data integrations from APIs, flat files, databases, and cloud systems