Role Description
The Data Engineer is responsible for designing, developing, and maintaining scalable data pipelines, data integration solutions, and enterprise data platforms to support business intelligence, analytics, reporting, and AI/ML initiatives. The role works closely with business stakeholders, solution architects, data architects, and application teams to ensure high-quality, reliable, and secure data is available across the organization.
Responsibilities
- Design, develop, and maintain end-to-end data pipelines for structured and unstructured data sources.
- Build and support data integration between enterprise systems, including SAP, Salesforce, CRM platforms, and cloud-based applications.
- Develop and optimize ETL/ELT processes to improve data quality, performance, and reliability.
- Implement data models and transformation logic in alignment with enterprise data architecture standards.
- Ensure data integrity, accuracy, and consistency across source and target systems.
- Collaborate with Data Architects, Business Analysts, and Solution Architects in designing scalable data solutions.
- Support analytics, reporting, dashboards, and AI/ML initiatives by providing trusted and governed datasets.
- Monitor and troubleshoot data pipelines, integration jobs, and platform performance issues.
- Implement data governance, security, privacy, and compliance requirements within data solutions.
- Maintain technical documentation, data dictionaries, and data lineage artifacts.
- Identify opportunities for automation and continuous improvement in data engineering processes.
Profile
- Bachelor's Degree in Computer Science, Information Technology, Software Engineering, Data Science, or related discipline.
- Minimum 3-8 years of experience in data engineering, data integration, or related fields.
- Strong understanding of data warehousing, data lakes, and modern data architecture principles.
- Experience with ETL/ELT tools and data integration platforms.
- Proficiency in SQL and experience with Python, Scala, or similar programming languages.
- Hands-on experience with cloud data platforms such as AWS, Azure, or Google Cloud.
- Experience integrating enterprise applications such as SAP, Salesforce, CRM, ERP, or similar business systems.
- Knowledge of data modeling concepts, including dimensional and relational modeling.
- Familiarity with data governance, data quality, and information security practices.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and stakeholder management capabilities.
- Preferred Qualifications
- Experience with SAP data structures and Salesforce data models.
- Experience in AWS services such as S3, Glue, Redshift, Lambda, or equivalent cloud technologies.
- Exposure to AI/ML data preparation and feature engineering.
- Knowledge of master data management (MDM) and enterprise data governance.
- Professional certifications in cloud, data engineering, or analytics technologies would be an advantage.
Key Competencies
- Data Integration & Engineering
- Data Modeling & Architecture
- ETL/ELT Development
- SQL & Data Analytics
- SAP & SFDC Data Management
- Cloud Data Platforms
- Problem Solving & Critical Thinking
- Stakeholder Engagement
- Data Governance & Security