Platform Architect

Positions: Platform Architect, Enterprise Data Engineering

Duration: Full time position

Location: Remote, open to nationwide candidates. (s)

Type: Remote work model

This is a senior level technical position that will lead a team or teams in Data Engineering with the focus being WorkDay data movement, data availability and surround application impacts.

1. This person must have had success in the past leading teams in Data Platforms Architecture and technical implementation of Data Pipelines, Database design (RDMS, Data Warehouses, Data Lakes) and Security.
2. This person must have hands-on experience, this role will be ~10 -20% hands-on and ~80% leadership and mentoring, thought leadership and architecture.
3. This person must have Snowflake Certification(s) and should have WorkDay Certification(s) with experience with Prism (WD reporting system).
4. This person must have implemented DBT package pipelines using Fivetran. No focus on Tableau or other reporting tools

Responsibilities:

• Participates in discussions with Product Owners, Business Analysts, and domain experts to determine requirements and model Data Engineering solutions.
• Works with Product Owners in ascertaining roadmap feasibility; delivers Data Engineering solutions based on roadmap that adhere to given constraints with focus on quality and time-to-market.
• Champions Enterprise Data Engineering Architecture, Patterns, and Guidance.
• Provides technical leadership and guidance on Data Engineering platform and tools.
• Uses empirical data to assess architectural requirements/constraints such as security, scalability, performance, availability, and redundancy.
• Ensures requirements can be met with minimal upfront design at an acceptable cost and with acceptable tradeoffs.
• Ensures physical and logical designs fit within our Enterprise Data Engineering architectural framework and conforms to accepted architectural standards.
• Identifies necessary interactions with other applications/services and defines Application Programming Interfaces (API) and service-level agreements (SLA).
• Formulates and evolves pattern-based Data Engineering designs appropriate for the solution with a clear separation of concerns.
• Grows and evolves the design, ensuring the integrity of the design is maintained over the course of a project.
• Communicates and champions the design across the team and fosters an environment of shared goals, collective ownership, and collaboration in building a design strategy.
• Possesses leadership skills needed to guide team members in delivering solutions that conforms to Data Engineering architecture and design.
• Coaches and mentors team members on Data Engineering design/implementation approaches and techniques.
• Brings consensus amongst team members on Data Engineering design and implementation strategy.
• Provides guidance on design and integration strategies on Data Engineering Practices in the form of standards documentation, examples, training, and consultancy.
• Publishes technical documentation such as high-level design, logical diagrams, support documentation based on need and value.
• Writes code and critiques developers code.
• Ensures Data Engineering designs and implementations fulfill not only functional needs but also non-functional needs such as security, maintainability, extensibility, testability, stability, configurability, and supportability.
• Evaluates and adopts third party products and platforms to solve Data Engineering problems.
• Participates in technical and leadership trainings as needed and/or recommended by supervisor.
• Coordinates Architectural evolutions with Enterprise and Solutions Architects.
• Works with teams designated to implement and improve DevOps CI/CD practices.
• Helps in release planning.

Qualifications:

• Bachelor s Degree in Computer Science, a related discipline, or four years of related work experience is required.
• Seven plus years of professional experience in Computer Science or a related field is required.
• Board knowledge of software development practice and procedures to build and implement analytics solutions across Data Engineering platforms/products (Azure, Snowflake, dbt, SQL Server, Tableau, PowerBI, Alation).
• Proficiency in database technologies like SQL and NoSQL, familiarity with database design and optimization for structured, semi-structured, and unstructured data.
• Working knowledge of Data Lakes, Data Warehousing Star & Snowflake schema, DevOps, CI/CD, Python and SQL.
• Apply best practices in Data Engineering to collect, move & transform, store, and analyze data at scale.
• Expertise in data integration & analytic methodologies, data modeling, and cloud services like computing, caching, storage, networking, and security.
• Progressive experience in new technology, programming, application analysis, and disaster recovery.
• Knowledge of Workday and/or Salesforce is a plus.
• Strong teamwork and collaborative skills.
• Strong verbal and written communication skills, with an ability to express complex technical concepts in business terms using diagrams and presentations as needed.
• Communicates tactfully and effectively and maintains positive and effective work relations with those encountered in the course of employment.
• Possesses a strong customer service attitude.
• Exhibits a passion for learning and continuous improvement. Takes responsibility for acquiring new skills and broadening knowledge.
• Exhibits a commitment to the utilization of defined standards and processes.

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