Data Engineer

Job Description

Key Accountabilities

• Participate in Data Management systems implementation projects: Data Lakehouse, Data Streaming, Metadata Management, Reference Data Management
• Develop data pipelines to bring new data to Enterprise Data Fabric
• Ensure data pipelines are efficient, scalable, and maintainable
• Comply with data engineering and development best practices (CI/CD, Code Management, Testing, Knowledge Management, Documentation etc.)
• Ensure that all Data Policies are met within Enterprise Data Fabric.
• Ensure that implemented systems correspond with target Data Architecture
• Support Data teams (DQ, Data Governance, BI, Data Science) in achieving their goals
• Maintain agile delivery process based on one of frameworks: Kanban, Scrum
• Ensure that SLAs with data consumers and data sources are maintained
• Implement all necessary monitoring, alerting

Other Accountabilities

• Software and Tools knowledge
• Python (Advanced level)
• Airflow or Apache NiFi
• K8s (OpenShift), Docker
• RDBMS: MS SQL Server, PostgreSQL, Oracle
• ETL (at least one of): SSIS, Informatica PowerCenter, IBM Datastage, Pentaho
• SQL – Advanced user (Stored Procedures, Window functions, Temp Tables, Recursive Queries)
• Git (GitHub/GitLab)

Skills

Key Interactions

• Familiar with following concepts:
• Data Warehousing (Star/Snowflake schemas)
• Data Lake
• Agile methodologies (Kanban, Scrum)
• Strong problem-solving skills

Competencies

• Adaptability/Flexibility
• Creativity/Innovation
• Decision Making/Judgment
• Dependability
• Initiative
• Integrity/Ethics
• Problem Solving/Analysis

Skills

• Ability to interact with internal and external stakeholders
• Ability to work under pressure
• Accuracy and attention to detail

Education

• Bachelor’s degree in Computer Science or equivalent