Key Responsibilities
- Data & Analytics Architecture Leadership. Lead the design and implementation of the data & analytics architecture, ensuring compliance, quality, and sustainable platform growth.
- End-to-End Data Pipeline Development. Build scalable end-to-end data pipelines to integrate and model datasets from various sources, meeting both functional and non-functional requirements.
- Technical Scope Management. Manage the technical scope and architecture of projects from inception to delivery and beyond.
- Stakeholder Collaboration. Collaborate with product, business, and functional stakeholders to understand data requirements and downstream analytics needs.
- Solution Ratification and Documentation. Responsible for ratifying technology solutions, producing concise design documents, and contributing to work estimates.
- Translation of Requirements. Translate business requirements and end-to-end designs into technical implementations based on system capabilities.
- Promotion of Best Practices. Define and promote reusable, extensible, scalable, and maintainable solutions, considering trade-offs between different factors.
- Communication. Communicate effectively at all levels about the importance of solution design and foster a data-driven culture within the team.
- Innovation. Drive innovation through a deep understanding of data, business drivers, and business needs.
Required Experience, Skills & Qualifications
- Experience. Around 8-10 years of relevant experience working with High-Performance Data Products or Data Systems as a Data Architect/Engineer.
- Proficiency. Advanced level proficiency in designing and developing data products, orchestration tools/services, and software engineering best practices.
- Cloud Platform Proficiency. Extensive experience in at least one cloud platform with Big Data services (e.g., EMR, Databricks).
- Database Expertise. Relevant experience in databases (columnar, NoSQL, and MPP databases) along with best practices in partitioning and clustering tables for efficient performance.
- Security Awareness. Should be aware of security compliances and design practices.
- Interpersonal Skills. Exceptional interpersonal, analytical, and communication skills, including the ability to explain and discuss DevOps concepts with colleagues and teams.
- CI/CD Pipeline Adherence. Fully adhere to and evangelize an entire CI/CD pipeline.
- API Development. Understands API development and use of JSON/XML as data formats.
- Data Engineering Tools. Knowledge and hands-on experience with data engineering tools for any cloud provider (e.g., Apache Kafka, Apache Flink, Amazon S3, AWS Glue, etc.).
This role requires a seasoned professional who can lead complex data architecture projects, collaborate effectively with stakeholders, and drive innovation in data solutions while adhering to best practices and security standards. Strong communication, technical expertise and a passion for data-driven decision-making are essential for success.