Data Engineer 181254

The Expertise and Skills You Bring

• Bachelor's or Master's degree in computer science, Engineering, or a related technical field.

• 7+ years of relevant work experience in data engineering or architecture.

• Strong SQL skills and knowledge of multiple RDBMS, specifically Snowflake (including SnowSQL), Postgres, SQL Server and Oracle.

• Proven experience building data pipelines using Python, with NiFi and dbt knowledge being a significant advantage.

• Experience in building Power BI Reports that transform data into aesthetically appealing visuals.

• Hands-on knowledge of AWS infrastructure, including S3, EC2, RDS, EKS, Batch, and CloudFormation.

• Deep understanding of data modeling principles, specifically 3NF and Star Schema models.

• Experience with CI/CD workflows using Jenkins and GitHub for automated deployment.

• Familiarity with workload scheduling and orchestration tools like Control-M.

• Proven data analysis skills to ensure data quality such as accuracy, consistency and completeness and to identify gaps and anomalies.

• Ability to work independently in an Agile environment (Scrum and Kanban) brings technical stories to completion.

• Excellent communication and presentation skills

Primary Responsibilities

• Design and build scalable data solutions, including data processing pipelines, migrations, and complex data modeling.

• Identify new development opportunities within a scalable public Cloud environment to enhance organizational capability.

• Collaborate with product owners and business partners to translate high-level requirements into actionable technical tasks.

• Analyze and manipulate datasets to ensure rigorous data integrity, accessibility, and security throughout the entire lifecycle.

• Serve as a technical mentor and thought leader, providing guidance and innovative solutions to the broader team.

• Integrate automated testing and continuous validation into the sprint cycle to ensure production reliability.

• Develop end-to-end solutions using distributed platform design patterns and modern analytics technologies.

• Support and enhance production systems, focusing on high performance, speed, and overall system reliability.