Senior Data Engineer; GenAI

Are you passionate about shaping the future of data-driven solutions? We are on the lookout for a highly experienced Senior Data Engineer to lead the development of advanced analytic data solutions leveraging the power of GenAI. In this pivotal role, you'll collaborate with business and technology leaders to design, build, and optimize data pipelines that drive critical decision-making across the organization.

If you have a proven track record in data engineering, a deep understanding of modern data platforms, and expertise in cloud architecture, SQL, Python, and containerization technologies, we want to hear from you. Come be a key player in transforming complex data challenges into innovative solutions in a fast‑paced, collaborative environment.

• You will be responsible for planning and leading research and development related to advanced analytic data solutions, leveraging GenAI.
• You will work with business and technology leaders to understand scope and requirements, business needs, and data from across the company in order to design and deliver the data pipelines necessary for our solutions.
• You will partner with the Decision Science Products, Decision Science, and customer teams on critical projects.
• Other activities include planning, estimating, design, development, testing, production rollout, and sustainment activities.
• You will also need to consult and collaborate with project team members, lead design reviews, do hands‑on development, and communicate with colleagues and leaders.

• 7+ years of overall experience in a data engineering development capacity using multiple environments (Dev, QA, Prod, etc.) and Dev Ops procedures for code deployment/promotion.
• Experience translating project scope and high‑level requirements into technical data engineering tasks.
• Experience defining solutions to sophisticated data engineering problems in support of advanced analytic processes.
• Experience with a variety of GenAI models, tools, and concepts.
• Understanding of Knowledge Graphs, Data Mesh, and other data sharing platforms.
• 3+ years using, designing, and building relational databases (preferably Snowflake or Postgre
  
  SQL).
• 3+ years of experience leading and deploying code using a source control product such as Git Lab/Git Hub.
• 2+ years of experience with job scheduling software like Apache Airflow, Amazon MWAA, Git Lab Runners, or UC4.
• Experience collaborating with multiple project teams in a fast‑paced environment.
• Experience with defining and estimating level‑of‑effort data engineering activities.
• Experience with project and sprint planning.
• Ability to communicate technical concepts and solutions to non‑technical team members.
• Experience designing and building data structures to support requirements.
• Multiple years of experience with ELT/ETL data pipeline development and maintenance.
• Multiple years of experience and expertise using SQL and Python.
• Experience using containerization technologies such as Docker or Kubernetes.
• Knowledgeable on cloud architecture and product offerings, preferably AWS.

• Experience collaborating with multiple project teams in a fast‑paced environment.
• Experience with defining and estimating level‑of‑effort data engineering activities.
• Experience with project and sprint planning.
• Ability to communicate technical concepts and solutions to non‑technical team members.
• Experience designing and building data structures to support requirements.
• Multiple years of experience with ELT/ETL data pipeline development and maintenance.
• Multiple years of experience and expertise using SQL and Python.
• Experience using containerization technologies such as Docker or Kubernetes.
• Knowledgeable on cloud architecture and product offerings, preferably AWS.

• BA/BS Degree Comp Sci/IS or related field.

• 401(k).
• Dental Insurance.
• Health insurance.
• Vision insurance.
• We are an equal‑opportunity employer and value diversity, equality, inclusion, and respect for people.
• The salary will be determined based on several factors, including, but not limited to, location, relevant education, qualifications, experience, technical skills, and business needs.