
Chief Data Innovation Officer
2 weeks ago
Job Title
Senior Data Architect
Job DescriptionAs a senior data architect, you will play a key role in driving technical leadership and communication with stakeholders within the data products team. You will be responsible for contributing high-quality, scalable, and maintainable code across data pipelines, APIs, and platform components.
- Drive development efforts by designing and delivering robust and future-proof data architectures that support analytics, APIs, and machine learning initiatives.
- Lead the technical execution of key projects, ensuring progress is clearly communicated and roadblocks are proactively addressed.
- Partner cross-functionally to co-develop architectural roadmaps, implementation plans, and go-live strategies that meet business requirements.
- Guide platform-level optimization, including cost efficiency, performance, reliability, and maintainability.
- Mentor engineers, fostering a strong technical culture and continuous learning environment.
You must have:
- Proven ability to communicate effectively with both technical and non-technical audiences, including customers, executives, and cross-functional teams.
- Experience tracking and clearly reporting project progress, milestones, and blockers to internal stakeholders and external partners.
- Technical depth to personally contribute to codebases and architecture discussions, while helping set standards across teams.
- A proactive and collaborative mindset focused on transparency, stakeholder engagement, and shared ownership of outcomes.
- Commitment to quality, scalability, and maintainability of systems through thoughtful design and testing.
This role offers:
- 10-20 years of development experience in data engineering, including direct contribution to 24x7 production systems.
- Advanced skills in Python and/or Golang, SQL, and current cloud data platforms (e.g., Databricks, BigQuery, Snowflake).
- Strong experience in communicating complex project plans and deliverables to both technical and business audiences.
- Track record of developing and operating scalable data pipelines, APIs, and data platform components in real-world environments.
- Experience working directly with external stakeholders or customers, either in consulting, enterprise data delivery, or technical leadership roles.
- Deep understanding of batch and real-time data architectures, data modeling, and data warehousing.
- Hands-on experience with cloud-native ecosystems (GCP, AWS, or Azure), CI/CD pipelines, and infrastructure as code.
- Experience with a broad range of cloud technologies.
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