IT Data Engineer

Work Flexibility: Onsite

Position summary:

Data Engineer is responsible for developing robust, scalable, high-performance data pipelines enabling the organization to extract valuable insights from large and complex datasets. This role will leverage Azure data services for data integration work, including developing a data model, maintaining a data lake and analytics environment, and writing scripts for data integration and analysis. This role will work closely and collaboratively with Data & Analytics team members to define requirements, mine and analyze data, integrate data from various sources, and deploy high-quality data pipelines to support the analytics needs of different Stryker business divisions and functions.

Essential duties & responsibilities: (detailed description)

• Data Architecture:
  • Design, implement, and maintain scalable and efficient data architecture to support business intelligence and analytics needs primarily utilizing Azure, Databricks, and Snowflake technology stack.
  • Collaborate with cross-functional teams to understand data requirements and translate them into effective data models.
• Data Pipeline Development:
  • Develop and maintain robust ETL/ELT processes to move and transform data from various sources into our data warehouse with key focus on Azure data factory pipelines.
  • Optimize and automate data pipelines to ensure high performance, reliability, and data integrity.
• Database Management:
  • Manage and optimize database systems, ensuring they meet performance and security requirements.
  • Implement data retention policies and archival strategies.
• Data Quality and Governance:
  • Establish and enforce data quality standards and best practices.
  • Work closely with data stewards to ensure data accuracy, completeness, and consistency.
• Performance Tuning:
  • Monitor and tune database and query performance for optimal efficiency.
  • Troubleshoot and resolve issues related to data processing and storage.
• Collaboration:
  • Collaborate with data scientists, analysts, and other stakeholders to understand their data needs and provide solutions.
  • Work closely with the IT team to integrate data engineering solutions into overall IT architecture.
• Documentation:
  • Document data engineering processes, workflows, and solutions.
  • Create and maintain documentation for data dictionaries, data lineage, and metadata.

Education & special trainings:

• Bachelor's Degree from an accredited university required, Bachelor’s degree in the areas of Computer science, Engineering, Information Systems, Business, or equivalent field of study preferred. 
• Azure based data engineering certifications preferred.

Qualifications & experience:

• Minimum 2-4 years of relevant experience required
• Ability to analyze business situations
• Proven experience as a Data Engineer with a strong focus on the Azure, Databricks, and Snowflake data analytics technology stack.
• Proficient in SQL and extensive experience with Azure services, Databricks, and Snowflake.
• Familiarity with big data and advanced data science technologies is a plus.
• Excellent problem-solving and troubleshooting skills.
• Strong communication and collaboration skills.

Travel Percentage: None