Data Platform Architect (Bellevue)

Data Platform Architect – Telecom Data Mediation

Location: Onsite – Bellevue, WA

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Position Summary

As a Data Platform Architect – Telecom Data Mediation, you will design, modernize, and support high-volume data mediation and ETL platforms that power billing, revenue assurance, analytics, and network operations. This onsite role in Bellevue, WA is ideal for a hands-on technical leader with deep experience in production data pipelines, Apache Kafka, distributed processing, and telecom data environments. You will guide architecture, mentor engineers, and help transform legacy data workloads into scalable, resilient, cloud-ready platforms.

Responsibilities

Design, build, and enhance ETL and data mediation pipelines that collect, parse, transform, and deliver network data, including CDRs, usage records, and performance metrics, to downstream billing, revenue assurance, and analytics systems.

Build, deploy, and support real-time streaming applications on Apache Kafka, including producers, consumers, stream processing, and data aggregation.

Develop and support batch data flows on distributed processing platforms such as Spark, Databricks, Hadoop, or similar technologies.

Modernize legacy on-premises data and mediation workloads to cloud-based and next-generation platforms.

Build configuration-driven parsers and transformation frameworks for diverse file formats, including ASN.1, XML, ASCII, and CSV, with minimal code change.

Create ingestion and delivery tooling to move data between source systems, data lakes, and external consumers using SFTP, APIs, Hive/Spark tables, and related technologies.

Develop feed auditing and monitoring capabilities to validate data completeness and accuracy, including Kafka throughput, lag, and delivery.

Troubleshoot data quality issues, pipeline failures, and performance bottlenecks using Linux/Unix tooling, SQL, logs, and end-to-end record tracing.

Maintain workflows, lookup tables, and configurations to support network and business rule changes.

Apply scripting and automation to improve deployment efficiency, operational consistency, and production reliability.

Define architecture, migration approach, and design standards for scalability, resiliency, configurability, and data quality.

Lead Kafka topic design, schema management, and design decisions for large-scale data platforms.

Conduct design reviews, provide technical direction, and mentor engineers on coding practices, debugging, and solution design.

Collaborate with engineering, billing, revenue assurance, and vendor teams to translate business and technical requirements into working solutions.

Maintain clear technical documentation, including solution designs, operational procedures, and runbooks.

Support additional duties and projects as assigned by business management.

Qualifications

Bachelor’s degree in Computer Science, Engineering, or a related field plus 5 years of related experience, or an advanced degree with 3 years of related experience.

For architect-level scope: 10+ years of experience, including designing or leading large-scale data platforms.

Hands-on experience building and supporting ETL, mediation, or data pipelines in production environments.

Strong programming skills in Java, Python, or C++.

Scripting experience with tools such as Shell, Perl, or Python.

Experience with distributed data processing technologies such as Spark, Databricks, Hadoop, or similar platforms.

Familiarity with streaming or messaging platforms such as Kafka, JMS, or similar technologies.

Strong SQL skills for data analysis, validation, troubleshooting, and reconciliation.

Experience working in Linux/Unix environments with log-based troubleshooting.

Ability to troubleshoot complex production issues, perform root-cause analysis, and drive improvements in performance, reliability, and data quality.

Strong communication skills with the ability to align technical goals to business priorities.

Collaborative mindset with the ability to build strong partnerships across engineering, billing, revenue assurance, vendor, and operations teams.

Customer-focused approach with a commitment to meeting internal and external stakeholder needs.

Analytical problem-solving skills with a logical, structured, and detail-oriented approach.

Strong sense of ownership, accountability, and operational discipline in production environments.

Preferred Qualifications

Experience with telecom data, including CDRs, network performance metrics, mediation, charging, or billing.

Experience building REST services or monitoring tools.

Experience with network data collection protocols such as SNMP or DIAMETER.

Familiarity with Kubernetes, containerized environments, and CI/CD pipelines.

Experience with commercial mediation or ETL platforms.

Exposure to data lakehouse and modern storage technologies such as Iceberg or S3-compatible storage.

Experience supporting telecom, IoT, or other high-volume distributed data environments.