Archer- Business Enablement Data Engineer

**Archer
- Business Enablement Data Engineer**

**Responsibilities**:

- Assists with creating, defining, and driving data engineering solutions to meet functional business requirements.
- Aggregates/ Creates data, data cleaning/manipulation, data science (e.g., geospatial, machine learning, predictive modeling, etc.), and visualizations.
- Solves various complex analytical challenges, sometimes dynamically balancing multiple internal projects simultaneously.
- Supports project teams with their analytics work in a “consultancy/expert” capacity on best practices concerning data & analytics engineering (e.g., on-prem databases & systems, data storage & warehousing, data management, big-data principles, analytics app prototyping, ETL)
- Develops and drive the data engineering roadmap needed to support the business.
- Collaborates with various stakeholders to continuously innovate on the tools, services, and data assets we can offer.
- Serves as the lead technical expert and thought leader in helping to innovate and develop offerings that require / benefit from advanced analytics skills or capabilities.
- Provides technical expertise and thought leadership on developing analytical tools, services, and data assets and contribute to building these areas directly when applicable.
- Creates production-quality data pipelines to develop and deploy scalable data science projects.
- Stays current on best-in-class software, tools, and techniques to ensure we can provide best-in-class solutions.
- Supports development and upskilling of staff on relevant software, tools, and techniques
- Develops and drive the technical roadmap on data engineering capabilities and infrastructure to ensure we operate a best-in-class Data & Analytics function.

**Qualifications**:

- Degree in a quantitative or business discipline or previous business experience preferred; examples include: Computer Science, Engineering, Information Technology, Data Science, Statistics, Mathematics, Operations Research, Economics
- Minimum 5 years of experience in applied data engineering; deep expertise in data engineering, as well as strong business and strategic analytical skills
- Ability to understand and articulate requirements to/from technical and non-technical audiences working alongside a data science & engineering team.
- Strong SQL & Python knowledge and familiarity with Big Data tools such as Spark & Scala; familiarity with Alteryx and Tableau
- Experience with data modeling, data structures (e.g., relational, and non-relational data), databases, and ETL/ELT processes and an in-depth understanding of large-scale data sets including both structured and unstructured data.
- Experience with designing, implementing, and delivering scalable data solutions and pipelines on one of the cloud platforms (e.g., AWS, Azure, GCP) and on-prem platforms such as Microsoft SQL Server
- Experience with building and deploying proprietary cloud-based analytics web apps.
- Hands-on experience in the development, deployment, and operation of integration technologies (e.g., APIs)
- Proficiency with data warehouses (e.g., Snowflake, Teradata, Redshift, Hadoop, BigQuery, etc.)
- Experience with containerization technologies (e.g., Docker, Kubernetes)
- Experience with DevOps, Git, CI/CD
- Experience directly managing another individual or a team.
- Prior experience in Strategic Data Consulting is preferred.

RSA is committed to the principle of equal employment opportunity for all employees and applicants for employment and to providing employees with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, and any other category protected by applicable country law.