Senior Data Engineer
Job Summary
We are looking for a skilled Data Engineer (2P level) with 3 – 5 years of experience in building, optimizing, and maintaining data pipelines, data integration workflows, and analytical data solutions. The ideal candidate will have solid hands-on expertise with Snowflake SQL, Azure Data Factory (ADF), Power BI, Power Automate, and Python.
Key Responsibilities
1. Data Pipeline Development & Maintenance:
- Design and maintain scalable ETL/ELT pipelines using ADF.
- Develop ingestion, transformation, and validation logic using Snowflake SQL and Python.
- Automate workflows using Power Automate.
2. Data Warehousing & Modeling:
- Build and optimize warehouse structures and models in Snowflake.
- Support data marts and reporting layers.
3. BI & Analytics Integration:
- Ensure seamless integration with Power BI.
- Collaborate with BI teams to optimize reporting models.
4. Data Quality, Governance & Monitoring:
- Implement validation routines and monitoring processes.
- Participate in governance and follow data security standards.
5. Collaboration & Stakeholder Engagement:
- Work with analytics teams and business stakeholders to understand requirements.
- Communicate pipeline status and issues.
6. Documentation:
- Document dataflows, ETL logic, and operational procedures.
Required Skills and Qualifications:
• Experience:
3 to 5 years of hands-on experience in data engineering, particularly in data warehouse development and ETL pipeline design.
• Education:
Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
• Technical Proficiency:
i. Proven experience with Azure Data Factory.
ii. Expertise in Snowflake for data warehousing, query optimization, and storage management.
iii. Strong SQL skills and experience with modern ETL tools (e.g., Azure Data Factory, Snowflake).
iv. Exposure to or experience with Power BI, especially in feeding and modeling data for dashboards.
v. Hands-on experience with Power Automate for workflow automation and integrations.
• Data Modeling:
Ability to design scalable data models for analytics use cases.
• Problem-Solving:
Strong analytical mindset to troubleshoot and optimize complex data issues.
• Collaboration:
Ability to work effectively with cross-functional teams, including data analysts, BI developers, and business stakeholders.
• Communication:
Excellent verbal and written communication skills to convey technical concepts to both technical and non-technical audiences.
Preferred Qualifications:
• Technical Proficiency:
Experience in designing and managing ELT/ETL workflows in Alteryx.
• Industry Knowledge:
Familiarity with the healthcare industry and its data analytics needs.