Technical Skills:
Skill | Years/Level of Experience |
ETL Development | 10+ years |
Data Engineering | 10+ years |
Required Qualifications
· 5+ of ETL/ELT development or data engineering experience, including leading complex transformation pipelines.
· Experience with ETL/ELT and data integration tools, specifically SAP Data Services and SAP Business Objects
· Advanced SQL expertise, including optimization, indexing strategies, and large scale data manipulation.
· Proven ability to lead design and architecture discussions for data integration solutions.
· Demonstrated experience translating complex business rules into scalable, enterprise ready transformation logic.
· Significant experience with scripting and automation (Python, Bash, PowerShell) for orchestration, validation, and operational support.
· Ability to independently diagnose and resolve complex workflow, performance, and data quality issues.
· Experience mentoring junior and mid-level developers.
Preferred Qualifications
· Deep experience with ETL/ELT and data integration platforms
· Expertise in SQL query tuning, stored procedures, partitioning strategies, and performance analysis.
· Strong mastery of Python or similar scripting languages for automation and data processing.
· Strong knowledge of data modeling, schema design, optimization, and large scale data architecture patterns.
· Advanced understanding of data warehousing, dimensional modeling, normalization/denormalization, ELT patterns, and MPP database environments.
· Experience with CI/CD pipelines, automated testing frameworks, and cloud data platforms (Azure, AWS, and Google Cloud Platform).
· Prior experience contributing to or defining engineering standards and best practices.
Education:
· Associate’s degree in computer science, Information Systems, Data Analytics, or related field (minimum).
· Bachelor’s degree strongly preferred
Key Responsibilities:
· Lead the design, development, testing, and maintenance of complex ETL/ELT workflows and data transformation pipelines across enterprise systems.
· Architect scalable data engineering solutions supporting analytics, reporting, and application integration.
· Establish and enforce best practices around data integration, modeling, pipeline development, and performance tuning.
· Develop comprehensive documentation for data flows, transformation logic, workflow patterns, and technical architecture.
· Proactively identify and implement pipeline optimization opportunities, including refactoring, architecting, and system performance improvements.
· Monitor enterprise data systems for integrity, performance, and stability; lead complex troubleshooting efforts.
· Refactor and modernize legacy ETL/ELT processes into scalable, cloud ready frameworks.
· Install, configure, and support advanced data related tools, platforms, and integrations.
· Lead integration, regression, performance, and functional testing for data systems to ensure enterprise reliability.
· Develop robust automation and orchestration scripts to eliminate manual processes and enhance operational scalability.
· Evaluate, recommend, and implement advanced tools, frameworks, and engineering controls.
· Collaborate with analysts, architects, developers, and senior stakeholders to gather, refine, and validate data engineering requirements.
· Represent data engineering needs in design reviews, solution architecture sessions, and project planning.
· Communicate complex technical concepts clearly to leadership, business partners, and cross functional teams.
· Lead security, governance, and data protection efforts across ETL/ELT workflows, including redundancy and backup design.
· Troubleshoot and resolve complex technical and network related issues affecting data pipelines across multiple platforms.
· Provide mentorship, guidance, and code reviews for junior and mid-level engineers.
Drive multi-platform integration efforts, deployments, and environment configuration across dev/test/prod.
