Data Engineer II

The position is responsible for designing, developing, and maintaining data pipelines and infrastructure. This role implements data integration, processing, and analytics solutions while collaborating with cross-functional teams to deliver efficient and scalable data systems., * Data Pipelines - Design, develop, and maintain data pipelines for efficient data processing and integration for real-time and batch-processing. Implement and optimize ETL processes to extract, load, transform and integrate data from various sources. Enhance data flows and storage solutions for improved performance

• Data Warehousing - Design and implement data warehouse structures. Ensure data quality and consistency within the data warehouse. Apply data modeling techniques for efficient data storage and retrieval
• Data Governance, Quality & Compliance - Implement data governance policies and procedures. Implement data quality frameworks, standards and documentation. Ensure compliance with relevant data regulations and standards
• Security & Access Management - Implement data security measures and access controls. Maintain data protection protocols
• Performance Optimization and Troubleshooting - Analyze and optimize system performance for large-scale data operations. Troubleshoot data issues and implement robust solutions
• Testing & Automation - Write unit test cases, validate the data integrity & consistency requirements, adopt automated data pipelines using GitLab, Github, CICD tools.
• Code Deployment & Release Management - Adopt release management processes to promote code deployment to various environments including production, disaster recovery, and support activities.
• Cross-Functional Collaboration - Collaborate with data scientists, analysts, and other teams to understand and meet data requirements. Participate in cross-functional projects to support data-driven initiatives

Data Management, Cross-Functional, Systems Scalability, Data Processing, Performance Management, Database Extract Transform and Load (ETL), Process Improvement, Data Storage, Data Quality, Data Recovery, Bachelor’’s Degree and 2 years of experience in Data engineering, data technologies, cloud platforms, High School Diploma or GED and 6 years of experience in Data engineering, data technologies, cloud platforms, Qualified candidates will have proven, hands-on production experience with most of the following:

• Building data pipelines using Medallion Architecture patterns
• Data ingestion using Qlik Replicate (snapshot, CDC, batch)
• Python development for data pipeline components
• dbt Cloud transformations, testing, and SQL development
• Snowflake ingestion and processing (Snowpipe, Tasks, Stored Procedures)
• RBAC and data masking concepts in Snowflake
• Cloud-native development on AWS or equivalent Azure platforms
• Experience with CI/CD pipelines (GitLab, GitHub Actions, etc.)
• Observability and monitoring tools such as Splunk or Dynatrace
• Experience in regulated or governance-heavy environments
• Relevant cloud or data platform certifications