Data Engineer | Seattle, WA

Tech Junction Ltd; Seattle (WA); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Tech Junction Ltd in Seattle, WA is seeking an experienced Data Engineer to design, build, and optimize distributed data pipelines for real-time and batch workloads, delivering low-latency data to analytics teams.

You will own end-to-end data workflows, tune queries, manage large-scale stores, and collaborate with data scientists and software engineers, ensuring scalable architectures and robust data governance.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline.
• Minimum of 5 to 7+ years of professional software and data engineering experience specializing in big data systems.
• Strong hands-on expertise in distributed data engineering, scalable data pipelines, and cloud data platforms.
• Proven practical proficiency in both real-time data streaming (e.g., Kafka, Spark Streaming) and batch data processing.
• Deep technical knowledge of database query optimization, indexing, and performance tuning in large-scale environments.
• Strong troubleshooting background with proven experience conducting Root Cause Analysis (RCA) on production failures.
• Exceptional analytical, problem-solving, and cross-functional communication capabilities.
• Mandatory legal eligibility to work in the United States with local presence in Seattle, WA or remote capability as applicable.

Responsibilities

• Design, build, test, and maintain scalable distributed data pipelines for real-time streaming and batch processing workloads.
• Develop and optimize big data architectures to handle massive throughput and low-latency data processing.
• Execute rigorous query optimization, performance tuning, and resource allocation across distributed data stores.
• Perform thorough Root Cause Analysis (RCA) and resolve complex data pipeline failures and latency bottlenecks.
• Integrate large-scale data lakes and data warehouses with enterprise data governance and security frameworks.
• Collaborate with cross-functional data scientists, analytics engineers, and software developers.
• Implement automated data quality checks, schema validation, and continuous integration pipelines.
• Maintain comprehensive technical documentation, data lineage graphs, and architectural diagrams.

Skills

Distributed data

Real-time streaming

Batch processing

Query optimization

Root Cause Analysis

Cross-functional communication

Troubleshooting

Education

Bachelor’s degree in CS/IT/Data Engineering

Tools

Kafka

Spark Streaming

Snowflake

dbt

Airflow

Spark

Hadoop

Docker

Kubernetes

Job description

Position Summary

We are actively seeking an experienced, high-caliber, and technical Data Engineer with strong expertise in distributed data engineering, real-time and batch processing, scalable data pipelines, and performance optimization to join our team in Seattle, WA on a full-time permanent basis. In this critical data infrastructure role, you will be responsible for building, maintaining, and scaling robust big data architectures and pipelines that process massive enterprise datasets. You will leverage your advanced proficiency in distributed systems, query optimization, and data streaming frameworks to ensure uncompromised data availability and low-latency processing. This opportunity offers competitive compensation, career growth, and executive visibility within a leading technology enterprise.

Detailed Job Description

As a Data Engineer supporting data architecture and analytics in Seattle, WA, you will take full operational, tactical, and technical ownership of end-to-end data pipeline development and big data platform optimization. Your day-to-day responsibilities include designing distributed data ingestion frameworks, implementing real-time streaming and batch processing workflows, and writing highly optimized queries for large-scale data stores. You will collaborate closely with data scientists, software developers, and analytics leads to troubleshoot data bottlenecks, perform root-cause analysis (RCA) on pipeline failures, and scale cluster resources. Furthermore, you will establish data governance protocols, implement automated testing suites, and maintain meticulous architectural documentation.

Key Responsibilities

• Design, build, test, and maintain scalable distributed data pipelines for both real-time streaming and batch processing workloads.
• Develop and optimize big data architectures to handle massive throughput and low-latency data processing.
• Execute rigorous query optimization, performance tuning, and resource allocation across distributed data stores.
• Perform thorough Root Cause Analysis (RCA) and resolve complex data pipeline failures and latency bottlenecks.
• Integrate large-scale data lakes and data warehouses with enterprise data governance and security frameworks.
• Collaborate with cross-functional data scientists, analytics engineers, and software developers.
• Implement automated data quality checks, schema validation, and continuous integration pipelines.
• Maintain comprehensive technical documentation, data lineage graphs, and architectural diagrams.

Required Qualifications & Skills

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline.
• Minimum of 5 to 7+ years of professional software and data engineering experience specializing in big data systems.
• Strong hands‑on expertise in distributed data engineering, scalable data pipelines, and cloud data platforms.
• Proven practical proficiency in both real‑time data streaming (e.g., Kafka, Spark Streaming) and batch data processing.
• Deep technical knowledge of database query optimization, indexing, and performance tuning in large-scale environments.
• Strong troubleshooting background with proven experience conducting Root Cause Analysis (RCA) on production failures.
• Exceptional analytical, problem‑solving, and cross‑functional communication capabilities.
• Mandatory legal eligibility to work in the United States with local presence in Seattle, WA or remote capability as applicable.

Nice-to-Have Skills

• Advanced postgraduate degrees in Computer Science, Data Science, or Analytics.
• Professional cloud certifications (e.g., AWS Certified Big Data, Google Cloud Professional Data Engineer, Databricks Certified Associate).
• Hands‑on experience with modern data stack tools (Snowflake, dbt, Airflow, Spark, Hadoop).
• Familiarity with containerization and orchestration platforms (Docker, Kubernetes).
• Strong background in MLOps and feature store integration.

Application Information

• Salary/Rate: Market Competitive / Enterprise Package
• Deadline: Open until filled
• Notice Period: Immediate to 2 Weeks
• Contract Duration: Permanent / Full-Time (Seattle, WA)

Recruitment Pro Tip

When applying for this Data Engineer position, ensure your CV explicitly highlights your distributed systems background, real‑time streaming expertise, query optimization projects, and RCA problem‑solving experience.