Role Description The Senior Staff Data Engineer is responsible for the design and implementation of numerous complex data flows to integrate operational systems, external and internal satellites and deliver data for analytics, AI, business intelligence (BI) systems and applications(s). Individuals in this role will: - Design, build and maintain a scalable data infrastructure and implement integration pipelines for multiple systems upstream and downstream; - Identify integration patterns and design architecture based on business requirements and platform capabilities which may include defining patterns for data streaming; - Lead projects for data assets and mentor and coach engineers while collaborating with other teams and business for technical consult; - Champion data engineering across platforms; - Establish standards for platform(s) being used and share across teams and engineers. This role will be Residence-Based in the US. Qualifications - Minimum of a Bachelor’s degree in Computer Science, Software Engineering, or related field, and significant professional software engineering experience. Additional professional experience will be suitable in lieu of a Bachelor’s degree; - Professional data engineering experience to include: - Experience working with Relational Database technologies, such as BigQuery, Oracle, Teradata, Postgres and/or Redshift; - Demonstrated expertise engineering data intensive solutions using streaming and resource based design principles; - Hands on experience using programming languages such as Python, Java and/or Golang; - Relevant certifications as applicable; - Demonstrated experience with data architecture and modeling, including designing both logical and physical models; - Strong organizational, interpersonal, written and oral communication skills and desire to work in a highly collaborative environment; - Strong problem solving, analytical and proven project delivery skills; - Ability to work collaboratively in a team environment; - Focused on data accuracy, timely delivery and attention to detail; - Ability to quickly learn upcoming technologies and familiarity with the relevant industry trends; - Deep knowledge and demonstrated experience with Google BigQuery and Google Cloud Platform; - Experience with version control and related tools Github, GitLab and IaC (like Terraform or others). Requirements - One of the following: - Bachelor’s degree in Computer Science, Software Engineering, or related field, with 5+ years of related professional software engineering experience, OR - Master's degree with 3 years of relevant experience, OR - PhD with 1 year of relevant experience; - 9+ years of relevant experience is an acceptable substitute for degree requirement. - Professional data engineering experience to include: - 5+ years of experience working with Relational Database technologies, such as BigQuery, Oracle, Teradata, Postgres and/or Redshift; - 3+ years of experience engineering data intensive solutions using streaming and resource based design principles; - 5+ years of experience using programming languages such as Python, Java and/or Golang. Benefits - Employees can expect to be paid a salary between $123,760 - $185,640. - Additional compensation may include a bonus or commission (if relevant). - Other benefits include health care, vision, dental, retirement, PTO, sick leave, etc. - If selected for this role, the offer may vary based on market data/ranges, an applicant’s skills and prior relevant experience, certain degrees and certifications, and other relevant factors. Company Description Bayer is an Equal Opportunity Employer/Disabled/Veterans and is committed to providing access and reasonable accommodations in its application process for individuals with disabilities.

• Collaborate with product managers, designers, infrastructure teams, and other stakeholders to develop data management strategy. • Build and maintain data pipelines that clean, transform, and aggregate data from disparate sources. • Build and maintain Tableau dashboards and custom reports. • Create and maintain technical documentation, including system design, APIs, usage guidelines, and best practices. • Identify and address performance bottlenecks across the entire application. • Identify architecture, design, and operational improvements to existing applications.

• Collaborate with team members to define requirements and translate them into scalable data models and pipelines. • Develop and maintain ELT pipelines, ensuring data reliability and scalability for business reporting and analytics use cases. • Work with raw data and transform it into structured, usable formats for analytics and reporting. • Build and optimize SQL-based data models using dbt and other ETL tools. • Identify and implement improvements in data delivery, processing performance, and system efficiency. • Contribute to the team’s technical vision and bring innovative solutions to enhance data systems. • Partner with data engineering teams to drive standardization and consistency of product data modeling, schemas and insights reporting across the entire company.

Role Description SAIC is searching for a motivated, career and customer-oriented Sr. AWS Data Engineer who will lead the next phase of our healthcare data platform modernization. This role is central to our evolution from an MSSQL XML object store toward a scalable, cloud-native AWS data architecture — one that enables business stakeholders and analysts to run performant, SQL-based reports and queries against our healthcare data seamlessly. This person will help evaluate and decide the right AWS data strategy for our platform. This is a 100% Remote role. - Evaluate and recommend the optimal AWS-native data storage and query architecture for our XML object store data — assessing options such as S3 + Athena, Aurora, DynamoDB, Redshift, and OpenSearch based on query patterns, reporting needs, cost, and scalability. - Design and build the reporting and query layer that allows business stakeholders and non-technical users to run relational SQL queries against healthcare data using familiar tooling. - Architect the migration path for XML object store data from MSSQL into the target AWS platform, defining storage formats, partitioning strategies, and data organization for optimal query performance. - Build and maintain AWS data catalog, schemas, and metadata management so that object store data is discoverable and queryable by business users. - Optimize query performance and cost across chosen AWS services — partitioning, compression, file formats, and query pattern tuning. - Work directly with business stakeholders and analysts to understand reporting requirements and translate them into durable, performant data models and query patterns. - Collaborate with backend C#/.NET engineers to ensure data flows cleanly from EDI processing pipelines into the new data layer. - Implement and maintain CI/CD pipelines for data infrastructure using AWS-native tooling (CodePipeline, CodeBuild, CodeDeploy). - Apply infrastructure as code (IaC) practices using AWS CDK, CloudFormation, or Terraform. - Document architecture decisions, data flows, and data dictionaries clearly for both technical and non-technical audiences. Company Description SAIC® is a premier Fortune 500® mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, civilian and intelligence markets includes secure high-end solutions in mission IT, enterprise IT, engineering services and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives. We are approximately 24,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.5 billion. For more information, visit saic.com . For ongoing news, please visit our newsroom .