Senior Data Platform Engineer — Architecture & Impact

Jobtailor

Arizona

On-site

USD 140,000 - 190,000

Full time

14 days+

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Job summary

Jobtailor in the United States is seeking a senior Data Platform Architect to design and implement scalable data systems across cloud environments. Collaborate with product teams to translate complex data needs into robust architectures, while guiding the lifecycle from design through production delivery.

The ideal candidate has extensive experience with data warehouses, big data, AI/ML model lifecycle, and modern data tooling.

Qualifications

Bachelor's degree in computer science or related technical field.
Eight+ years of relevant related experience.
7+ years in complex data platform, distributed systems, SaaS, cloud solutions, microservices.
6+ years in Data Warehouse, Big Data, real-time & batch processing, data standards.
4+ years in Business Intelligence solutions.
2+ years in AI/ML model development lifecycle.
Experience delivering business-critical systems to market.
Ability to influence and work in a collaborative team environment.
Experience designing/developing scalable systems.
Extensive experience with Data Warehouse (Star/Snowflake), SQL Server, Big Data stacks (HDFS, ElasticSearch), ETL with IBM Infosphere, reusable frameworks.
Experience with Python, Spark, PySpark, R, DataRobot.
Experience with event-driven architectures and messaging (Pub/Sub, Kafka, RabbitMQ).
Cloud proficiency (GCP, AWS, Azure).
Knowledge of CI/CD, testing, secure coding, SDLC, Agile/LEAN, DevOps.
Attention to detail and strong analytical skills.

Responsibilities

Build data strategy for broad or complex requirements extending beyond the direct team.
Participate in strategic development of methods, techniques, and evaluation criteria for projects and programs.
Drive data architecture, design, prototyping and implementation for product needs and data strategy.
Provide leadership in building a technical plan and backlog, guiding execution to production delivery.
Lead a broad functional area and coordinate with team members for planning.
Represent engineering in cross-functional sessions and advocate sound arguments.
Influence others to reach agreement or behavior changes.
Collaborate with product managers, designers, and other engineering groups to build new features.
Own features or systems and maintain long-term health of related systems.
Support Support and Operations teams in resolving production issues quickly.
Develop and implement tests for quality, performance, and scalability.
Continuously improve engineering data standards, tooling, and processes.
Contribute to risk management and data confidentiality.