• Develop and maintain data pipelines required for the extraction, transformation, cleaning, pre-processing, aggregation, and loading of data from a wide variety of data sources using Python, SQL, DBT, and other data technologies • Design, implement, test, and maintain data pipelines/ new features based on stakeholders’ requirements • Develop/maintain scalable, available, quality-assured analytical building blocks/datasets by close coordination with data analysts • Optimize/ maintain workflows/ scripts on present data warehouses and present ETL • Design / develop/maintain components of data processing frameworks • Build and maintain data quality and durability tracking mechanisms to provide visibility into and address inevitable disruptions in data ingestion, processing, and storage • Translate deeply technical designs into business-appropriate representations as well as analyze business needs and requirements ensuring the implementation of data services directly correlates to the strategy and growth of the business • Focus on automation use cases, CI/CD approaches, and self-service modules relevant to data domains • Address questions and concerns from downstream data consumers through appropriate channels • Create data tools for analytics and BI teams that assist them in building and optimizing our product into an innovative industry leader • Stay up to date with data engineering best practices, and patterns, evaluate and analyse new technologies, capabilities, and open-source software in the context of our data strategy to ensure we are adapting, extending, or replacing our core technologies to stay ahead of the industry • Contribute to Analytics engineering process

Role Description We are looking for an experienced Oracle DBA / Data Processing Specialist who combines strong database administration expertise with hands-on data processing capabilities. In this role, you will be responsible for ensuring the stability, performance, and availability of Oracle production environments, while executing and delivering accurate client data in a fast-paced marketing data setting. This position requires a highly reliable, detail-oriented professional who can effectively manage multiple priorities. - Administer and monitor Oracle production databases (logs, backups, performance, and security) - Manage users, access controls, patching, and database recovery processes - Develop and optimize database objects (PL/SQL, SQL tuning) - Analyze performance using AWR, ADDM, and execution plans - Execute data processing tasks: data loading, transformation, validation, and client delivery - Ensure data quality through QC processes, documentation, and reporting - Support development teams and respond to client data requests - Participate in change management, disaster recovery planning, and process improvements Qualifications - 3+ years of hands-on experience as an Oracle DBA in production environments - Strong proficiency in PL/SQL (procedures, functions, triggers, packages) - Experience working with UNIX/Linux and shell scripting - Solid knowledge of Oracle Data Guard, RAC, and OEM - SQL tuning and performance analysis - AWR and ADDM tools - RMAN backup and recovery - Oracle security patching (quarterly cycles) - Table, index, and schema design - Experience handling client data files (loading, transformation, vendor transfers) - Background in technical documentation and data quality control Core Competencies - Strong attention to detail and data accuracy - Ability to manage multiple priorities in a fast-paced environment - Effective communication with technical teams and clients - Highly organized and self-directed - Proactive mindset with continuous learning approach Nice to Have - Experience with cloud or hybrid Oracle environments - Knowledge of SQL Server or PostgreSQL

• Own the multi-region data architecture across six AWS-native engines: Aurora MySQL, Cassandra, ElastiCache (Redis / Valkey), DynamoDB, DocumentDB, and Neptune. For each, define the cross-region replication pattern (Aurora Global Database, DynamoDB Global Tables, DocumentDB Global Clusters, Cassandra multi-DC, MemoryDB or Valkey global datastore, Neptune Global Database) and the operational model that supports it. • Define and own the per-tier RTO and RPO commitments (Tier 0 / Tier 1 / Tier 2) and the cutover and failback runbooks and perform validation using Fault Injection Service / Game Days. • Sequence the data-layer cutover across all three program phases. Identify strong-consistency vs eventual-consistency decisions per workload, and where active-active is feasible vs where region-sharded ledgers or single-writer with replicated read-models is the right pattern. • Lead a team of Database Engineers across the engines. Set the technical bar, review designs, and unblock implementation. Partner with the client's DB and SRE leadership on architecture decisions and Operational Readiness Reviews. • Translate data-layer constraints into the application decomposition strategy. Where the monolith is being broken up into microservices, advise on data ownership boundaries (DDD-aligned), strangler-fig extraction patterns, CDC pipelines (DMS, DDB Streams, Kafka Connect), and the event-based contracts that decouple services from the monolith. • Produce the audit-grade artifacts the client and their regulators expect: replication runbooks, DR test evidence, RTO and RPO measurement methodology, and Well-Architected Reliability Pillar alignment.

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.