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Senior Data Engineer
Skills
Business IntelligenceConsumer TextilesData AnalyticsData IntegrityDatabasesModelingProject Implementation
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 8+ years of professional experience in Data Engineering Backend Platform Engineering or large-scale data infrastructure
- 3+ years of client-facing or consulting-focused data engineering experience
- Advanced SQL expertise including schema design query optimization complex views CTEs window functions deduplication strategies and data modeling
- Strong Python experience for ETL development automation PySpark and data processing workflows
- Hands-on experience building and maintaining enterprise-scale ETL/ELT pipelines in production environments
- Experience integrating data from REST APIs GraphQL endpoints and webhook-based systems
- Strong understanding of data quality practices validation processes anomaly detection and data governance
- Experience working across multiple concurrent client engagements with varying levels of data maturity
- Excellent documentation and communication skills including data dictionaries lineage documentation and technical handoffs
- Strong ownership mindset and the ability to operate independently in fast-paced environments
Nice to have
- Client-facing
- Detail-oriented
- Independent
- Collaborative
- Mentor-minded
- Quality-focused
Day to day
- Design and maintain scalable ETL/ELT pipelines across enterprise client environments
- Build robust SQL views schemas and transformation logic to support analytics and Power BI solutions
- Profile source data validate integrity and document lineage data dictionaries and operational handoffs
- Integrate REST API GraphQL and webhook data sources while supporting Microsoft Fabric and Databricks environments