Staff Data Engineer

Bayer•Tulsa, OK

20h

About The Position

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice. Staff Data Engineer YOUR TASKS AND RESPONSIBILITIES The primary responsibilities of this role, Staff Data Engineer are to: A staff data engineer designs and leads the implementation of data flows to connect operational systems, data for analytics and business intelligence (BI) systems. Individuals in this role will: Recognize opportunities to reuse existing data flows; Lead the build of data streaming systems; Optimize the code to ensure processes perform optimally; Lead work on database management; Communicating Between Technical and Non-Technical Colleagues Communicate effectively with technical and non-technical stakeholders; Support and host discussions within a multidisciplinary team, with potentially difficult dynamics; Be an advocate for the team externally, and can manage differing perspectives. Data Analysis and Synthesis Undertake data profiling and source system analysis; Present clear insights to colleagues to support the end use of the data. Data Development Process Design, build and test data products that are complex or large scale; Build teams to complete data integration services. Data Innovation Understand the impact on the organization of emerging trends in data tools, analysis techniques and data usage; Data Integration Design Select and implement the appropriate technologies to deliver resilient, scalable and future-proofed data solutions and integration pipelines; Data Modeling Produce relevant data models across multiple subject areas; Explain which models to use for which purpose; Understand industry-recognized data modelling patterns and standards, and when to apply them; Compare and align different data models. Metadata Management Design an appropriate metadata repository and present changes to existing metadata repositories; Understand a range of tools for storing and working with metadata; Provide oversight and advice to more inexperienced members of the team. Problem Resolution Respond to problems in databases, data processes, data products and services as they occur; Initiate actions, monitor services and identify trends to resolve problems; Determine the appropriate remedy and assist with its implementation, and with preventative measures. Programming and Build Use agreed standards and tools to design, code, test, correct and document moderate-to-complex programs and scripts from agreed specifications and subsequent iterations; Collaborate with others to review specifications where appropriate. Technical Understanding Understand the core technical concepts related to the role, and apply them with guidance; Testing Review requirements and specifications, and define test conditions; Identify issues and risks associated with work; Analyze and report test activities and results.

Requirements

Proficiency in programming language such as Python or Java
Experience with Big Data technologies such as Hadoop, Spark, and Kafka
Familiarity with ETL processes and tools
Knowledge of SQL and NoSQL databases
Strong understanding of relational databases
Experience with data warehousing solutions
Proficiency with cloud platforms
Expertise in data modeling and design
Experience in designing and building scalable data pipelines
Experience with RESTful APIs and data integration

Nice To Haves

Relevant certifications (e.g., GCP Certified, AWS Certified, Azure Certified)
Bachelor’s degree in Computer Science, Data Engineering, Information Technology, or a related field
Strong analytical and communication skills
Ability to work collaboratively in a team environment
High level of accuracy and attention to detail

Responsibilities

Recognize opportunities to reuse existing data flows
Lead the build of data streaming systems
Optimize the code to ensure processes perform optimally
Lead work on database management
Communicate effectively with technical and non-technical stakeholders
Support and host discussions within a multidisciplinary team, with potentially difficult dynamics
Be an advocate for the team externally, and can manage differing perspectives.
Undertake data profiling and source system analysis
Present clear insights to colleagues to support the end use of the data
Design, build and test data products that are complex or large scale
Build teams to complete data integration services
Understand the impact on the organization of emerging trends in data tools, analysis techniques and data usage
Select and implement the appropriate technologies to deliver resilient, scalable and future-proofed data solutions and integration pipelines
Produce relevant data models across multiple subject areas
Explain which models to use for which purpose
Understand industry-recognized data modelling patterns and standards, and when to apply them
Compare and align different data models
Design an appropriate metadata repository and present changes to existing metadata repositories
Understand a range of tools for storing and working with metadata
Provide oversight and advice to more inexperienced members of the team
Respond to problems in databases, data processes, data products and services as they occur
Initiate actions, monitor services and identify trends to resolve problems
Determine the appropriate remedy and assist with its implementation, and with preventative measures
Use agreed standards and tools to design, code, test, correct and document moderate-to-complex programs and scripts from agreed specifications and subsequent iterations
Collaborate with others to review specifications where appropriate
Understand the core technical concepts related to the role, and apply them with guidance
Review requirements and specifications, and define test conditions
Identify issues and risks associated with work
Analyze and report test activities and results