Description

Key Responsibilities

1. EDW Architecture & Data Engineering

• Design and implement scalable data integration and transformation frameworks for the Enterprise Data Warehouse.
• Architect and optimize ETL/ELT pipelines using SAP BODS and IBM DataStage.
• Develop and maintain robust data models (Star/Snowflake schemas, SCD implementation).
• Ensure high availability, reliability, and performance of data pipelines.
• Implement data governance, security, and compliance standards.

2. ETL Development & Optimization

• Develop complex data workflows and transformations.
• Perform performance tuning of ETL jobs and SQL queries.
• Optimize batch processing and scheduling using Redwood.
• Implement error handling, logging, and monitoring mechanisms.
• Manage incremental loads and data reconciliation processes.

3. Database & SQL Development

• Write and optimize complex SQL queries, stored procedures, and functions.
• Work extensively with Oracle databases and related technologies.
• Design and manage indexing strategies and query optimization.
• Support database performance analysis and tuning.

4. Leadership & Team Management

• Lead and mentor a team of data engineers.
• Conduct code reviews and enforce development standards.
• Drive technical best practices and architecture governance.
• Collaborate with cross-functional teams including BI, Analytics, and Application teams.
• Participate in sprint planning, estimation, and technical roadmap discussions.

5. Stakeholder Collaboration

• Work closely with business stakeholders to gather and translate requirements into technical solutions.
• Provide technical guidance and solution recommendations.
• Ensure alignment between enterprise data strategy and business goals.
• Support production issue resolution and root cause analysis.

Required Skills

Technical Expertise

• Strong experience with SAP BODS
• Hands-on experience with IBM DataStage
• Experience with Redwood scheduling
• Advanced SQL development
• Strong expertise in Oracle database
• Deep understanding of Enterprise Data Warehouse architecture

Data Engineering Concepts

• Data modeling (Star/Snowflake schema, SCD Types)
• ETL/ELT best practices
• Data quality frameworks
• Performance tuning and optimization
• Data security and governance standards

Preferred / Good to Have

• Experience with modern cloud data platforms (Azure, AWS, GCP)
• Knowledge of Snowflake, Databricks, or Synapse
• CI/CD implementation for data pipelines
• Exposure to data cataloging and metadata management tools
• Experience in Agile/Scrum methodologies

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.
• 5+ years of experience in Data Engineering.
• 2+ years of experience in leading technical teams

Key Skills

Education

Bachelor's degree