p/>If you are applying to perform work for Medtronic, Inc. (“Medtronic”) in any position which will involve performing at least two (2) hours of work on average each week within the unincorporated areas of Los Angeles County, you can find herea list of all material job duties of the specific job position which Medtronic reasonably believes that criminal history may have a direct, adverse and negative relationship potentially resulting in the withdrawal of a conditional offer of employment.
The following benefits and additional compensation are available to those regular employees who work 20+ hours per week: Health, Dental and vision insurance, Health Savings Account, Healthcare Flexible Spending Account, Life insurance, Long-term disability leave, Dependent daycare spending account, Tuition assistance/reimbursement, and Simple Steps (global well-being program).
Implementing data integration solutions using AWS Glue, AWS Lambda, Azure Data Factory, Azure Functions, GCP Functions, GCP Dataproc, Dataflow and other relevant services • Designing and managing data warehouses and data lakes, verifying data is organized and accessible • Monitoring and troubleshooting data pipelines, data warehouses and workflows to verify data quality, system reliability, performance and cost management • Implementing IAM roles and policies to manage access and permissions within AWS, Azure, GCP • Use AWS CloudFormation, Azure Resource Manager templates, Terraform for infrastructure as code (IaC) deployments • Use AWS, Azure and GCP DevOps services to build and deploy DevOps pipelines • Implementing data security practices using AWS, Azure, GCP, Snowflake or Databricks • Improving Cloud resources for cost, performance, and scalability • Proficiency in SQL and experience with relational databases • Proficient in programming languages such as Python, Java, or Scala • Familiarity with big data technologies like Hadoop, Spark, or Kafka is a plus • Experience with machine learning and data science workflows is a plus • Knowledge of data governance and data security practices • Demonstrating analytical, problem-solving, and communication skills • Having the ability to work independently and as part of a team in a fast-paced environment • Applying modern, cloud-based technology skills, ability to research emerging trends, analyst publications, and adoption of modern technologies in solution architectures • Collaborating and contributing as a team member: understanding personal and team roles, contributing to a positive working environment by building proven relationships with team members, proactively seeking guidance, clarification and feedback • Prioritizing and handling multiple tasks, researching and analyzing pertinent client, industry and technical matters, utilizing problem-solving skills, and communicating effectively in written and verbal formats to various audiences (including various levels of management and external clients) in a professional business environment • Coaching and collaborating with associates who assist with this work, including providing coaching, feedback and guidance on work performance. • Certification in Cloud Platforms [e.g., AWS Solutions Architect, AWS Data Engineer, Google Professional Cloud Architect, GCP Data Engineer Microsoft Azure Solutions Architect, Azure Data Engineer Associate, or Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus • Designing and implementing thorough data architecture strategies that meet the current and future business needs • Developing and documenting data models, data flow diagrams, and data architecture guidelines • Verifying data architecture is compliant with data governance and data security policies • Collaborating with business stakeholders to understand their data requirements and translate them into technical solutions • Evaluating and recommending new data technologies and tools to enhance data architecture • Building, maintaining, and improving ETL/ELT pipelines for data ingestion, processing, and storage across batch and real-time data processing • Building, maintaining, and improving Data Quality rules leveraging DQ tools and/or other ETL/ELT tools • Developing and deploying scalable data storage solutions using AWS, Azure and GCP services such as S3, Amazon RDS, DynamoDB, Azure Data Lake Storage, Azure Cosmos DB, Azure SQL DB, GCP Cloud Storage etc.