Responsibilities

Design, evolve, and maintain scalable cloud data architectures, data lakes, and enterprise data warehouses.
Build and support data integration between enterprise systems, including SAP, Salesforce, CRM platforms, and cloud-based applications.
Lead the development of batch and streaming ETL/ELT pipelines processing high-volume, multi-source data.
Implement framework solutions for data monitoring, lineage, data masking, encryption, and role-based access controls
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 8-12 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

Lead Data Engineer