Job Description: Data Architect Aftersales Service & Repair (Truck Industry)
Location: Renton, WA (5 Days onsite)
About the Role
We are seeking a skilled Data Architect to lead the migration, analysis, and reporting of service and repair data, including external data sourced from dealers in the truck industry. This role plays a critical part in enabling data-driven decision-making for our Aftersales operations by designing and implementing robust data pipelines, data models, and real-time reporting solutions.
Key Responsibilities
- Design and architect scalable data ingestion pipelines to process service and repair data from multiple sources, including external dealer data streams.
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Ingest real-time data using Confluent Kafka and ensure reliable, high-throughput data flow.
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Utilize Google Dataflow to perform data cleansing, normalization, and transformation operations.
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Model and optimize data storage in Snowflake to support efficient querying and reporting.
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Develop and maintain interactive and insightful dashboards using Tableau to enable business users to monitor Aftersales service performance.
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Implement real-time reporting capabilities by pushing transformed data through APIs to dashboards.
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Collaborate closely with data engineers, analysts, and business stakeholders to understand data requirements and deliver optimal solutions.
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Establish and enforce data governance, quality, and security standards.
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Continuously improve data architecture to support scalability, performance, and evolving business needs.
Required Qualifications
- Proven experience as a Data Architect or similar role in data-intensive environments.
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Strong expertise in data ingestion technologies, especially Confluent Kafka.
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Hands-on experience with Google Dataflow (Apache Beam) for data processing and transformation.
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Deep knowledge of cloud data warehousing concepts, with proficiency in Snowflake.
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Experience creating reports and dashboards using Tableau.
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Solid understanding of data modeling techniques (star schema, snowflake schema, normalized forms).
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Familiarity with API integration for real-time data delivery.
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Strong problem-solving skills and attention to data quality and reliability.
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Excellent communication skills and ability to translate technical concepts for business stakeholders.
Preferred Qualifications
- Experience in the automotive or truck industry, particularly in Aftersales service data.
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Knowledge of additional cloud platforms and data tools (e.g., AWS, GCP, Azure).
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Programming skills in Python, SQL, or Java.