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Job Description & How to Apply Below
Job Title:
Data Integration Engineer (Snowflake / DBT / Oracle EBS)
Experience:
5+ Years
Location:
Pune/Nagpur
Job Summary
The ideal candidate will have strong hands-on experience with Snowflake SQL, DBT, Oracle E-Business Suite (EBS), and enterprise-grade data transfer mechanisms such as SFTP and batch/real-time integrations. A solid understanding of manufacturing and ERP data is critical.
Key Responsibilities
- Design, develop, and maintain end-to-end data integration pipelines between Oracle EBS, Snowflake, and other enterprise systems
- Build and optimize SQL-based transformations in Snowflake using DBT following best practices
- Manage and support data ingestion frameworks using file-based transfers (SFTP), batch loads, and near real-time feeds
- Ensure reliable movement of live and transactional data with proper reconciliation, validation, and error handling
- Work closely with ERP, manufacturing, finance, and operations teams to understand data sources and integration needs
- Develop and maintain data models that support reporting, analytics, and operational use cases
- Monitor data pipelines for performance, latency, and failures; implement proactive alerting and recovery mechanisms
- Ensure data quality, consistency, and completeness across integrated systems
- Document data flows, mappings, transformation logic, and operational runbooks
- Support audits, compliance, and security requirements related to enterprise data movement
Required
Skills & Qualifications
- 5+ years of hands-on experience in data integration / data engineering roles
- Strong expertise in Snowflake SQL (performance tuning, complex joins, analytics functions)
- Proven experience with DBT (models, tests, macros, incremental loads, deployments)
- Solid working knowledge of Oracle E-Business Suite (EBS) data models (Finance, Manufacturing, Supply Chain preferred)
- Strong understanding of ERP-driven data flows and enterprise data architectures
- Hands-on experience with SFTP-based data transfers, flat files, CSVs, and structured data formats
- Knowledge of data movement concepts such as CDC, batch vs near-real-time processing, and scheduling
- Experience handling high-volume and live operational data with strict SLAs
- Strong SQL debugging, data validation, and reconciliation skills
- Familiarity with Unix/Linux environments and basic shell scripting
Nice-to-Have Skills
- Experience in manufacturing or jewelry/retail manufacturing domains
- Exposure to ETL/ELT tools or orchestration frameworks (Airflow or similar)
- Knowledge of data security, encryption, and secure file transfer standards
- Experience supporting downstream BI or analytics platforms
- Understanding of master data, transactional data, and reference data management
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