Position Summary
The Data Engineer is responsible for designing, building, and optimizing scalable data pipelines, data integration solutions, and cloud-based data platforms that support enterprise analytics, reporting, and AI/ML initiatives.
This role serves as a technical expert in data engineering, ensuring reliable data ingestion, high-quality data assets, and efficient data processing while collaborating closely with architects, analysts, and business stakeholders.
Key Responsibilities
Data Engineering & Development
- Design, develop, and maintain scalable and high-performance data pipelines.
- Build and optimize ETL/ELT processes to ingest, transform, and deliver data across enterprise platforms.
- Develop and maintain reusable data engineering frameworks and components.
- Implement data integration solutions for structured and unstructured data sources.
- Support modern cloud-based data platform initiatives.
- Data Ingestion & Pipeline Operations Develop and manage batch and real-time data ingestion pipelines.
- Monitor and optimize pipeline performance, reliability, and scalability.
- Troubleshoot data processing issues and implement corrective actions.
- Automate data workflows and orchestration processes.
- Ensure timely and accurate data delivery to downstream consumers.
Data Quality & Governance
- Implement data validation, reconciliation, and quality controls.
- Support data governance standards, metadata management, and data lineage initiatives.
- Identify and resolve data quality issues and causes.
- Contribute to data observability and monitoring solutions.
- Ensure compliance with organizational data management standards.
- Meridian Platform Support & Implementation Support the implementation and enhancement of Meridian data solutions.
- Develop integrations and data pipelines supporting Meridian initiatives.
- Collaborate with stakeholders to translate business requirements into technical solutions.
- Ensure successful deployment, testing, and operational support of Meridian-related capabilities.
Technical Leadership & Collaboration
- Provide technical guidance and mentorship to junior and mid-level engineers.
- Participate in architecture reviews, design sessions, and code reviews.
- Collaborate with data architects, product owners, analysts, and business stakeholders.
- Promote engineering best practices, automation, and continuous improvement.
- Document technical designs, standards, and operational procedures.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
- 5+ years of experience in Data Engineering or related disciplines.
- Strong experience designing and developing enterprise data pipelines and integration solutions.
- Expertise in SQL and one or more programming languages such as Python, Scala, or Java.
- Experience with ETL/ELT frameworks, data warehousing, and data lake architectures.
- Experience with cloud platforms such as Azure, AWS, or Google Cloud. Knowledge of workflow orchestration tools such as Airflow, Azure Data Factory (ADF), or similar platforms.
- Strong understanding of data quality, data governance, and monitoring concepts.
- Experience troubleshooting and optimizing large-scale data processing solutions.