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Data Engineer | Octagon IT | Remote (PST Zone)

November 3, 2026

Position Summary

Octagon IT is actively seeking an experienced, high-caliber, and technical Data Engineer with a strong professional background in data pipeline engineering, big data processing, and cloud analytics to join our client engineering team on a full-time permanent remote basis (with a preference for local candidates in the PST zone). In this critical data infrastructure and analytics role, you will be responsible for designing, building, securing, and scaling robust data pipelines, data warehouses, and automated ETL workflows. You will leverage your deep specialist expertise in SQL, Python, Databricks, and Amazon Web Services (AWS) to deliver uncompromised data reliability, high throughput, and operational excellence. This opportunity offers competitive compensation, executive technical visibility, and exceptional career growth prospects within a premier global IT recruitment and consulting enterprise.

Detailed Job Description

As a Data Engineer supporting Octagon IT remotely, you will take full operational, tactical, and technical ownership of data pipeline architecture, big data processing, cloud data warehousing, and ETL/ELT workflow execution across mission-critical analytics platforms. Your day-to-day responsibilities include designing, developing, testing, and maintaining scalable data pipelines and data ingestion frameworks utilizing Python and advanced SQL, building, optimizing, and managing big data processing pipelines and analytics clusters utilizing Databricks and Spark frameworks, provisioning, administering, and securing cloud data infrastructure and storage services across Amazon Web Services (AWS), collaborating closely with cross-functional software engineering, data science, product, and executive stakeholder squads in Agile sprint cycles, conducting rigorous data quality audits, performance tuning, and query optimization across large-scale datasets, preparing comprehensive technical documentation of data models, pipeline topologies, and operational runbooks, and managing application requirements. You will utilize your proactive troubleshooting and analytical problem-solving skills to resolve complex data pipeline failures and latency bottlenecks under strict service level agreements. Furthermore, you manage application requirements ensuring strict compliance with the remote PST timezone preference.

Key Responsibilities

Design, develop, test, optimize, and maintain scalable data pipelines and automated ETL/ELT integration workflows.
Build and maintain high-performance big data processing pipelines and analytics notebooks utilizing Databricks.
Author complex, highly optimized SQL queries, stored procedures, and data transformation scripts.
Develop robust data automation and pipeline orchestration scripts utilizing Python programming.
Administer, secure, and optimize cloud data storage, compute instances, and serverless infrastructure on Amazon Web Services (AWS).
Monitor data ingestion jobs, database query performance, and pipeline execution logs proactively.
Collaborate seamlessly with cross-functional software engineering, data science, and business analytics squads.
Maintain accurate, comprehensive technical documentation of data schemas, pipeline architectures, and operational runbooks.

Required Qualifications & Skills

Bachelor’s degree in Computer Science, Data Science, Software Engineering, Information Technology, or a related technical discipline.
Minimum of 3 to 6 years of progressive professional experience in data engineering, big data analytics, and ETL development.
Strong, demonstrable hands‑on professional expertise in advanced SQL programming and data modeling.
Comprehensive working knowledge and practical proficiency in Python scripting for data engineering and automation.
Deep practical experience building and optimizing big data processing workflows utilizing Databricks and Apache Spark.
Solid practical experience provisioning, configuring, and managing cloud infrastructure on Amazon Web Services (AWS).
Exceptional analytical, troubleshooting, debugging, and problem‑solving capabilities under high‑pressure conditions.
Excellent written and verbal English communication skills with strong cross‑functional collaboration and stakeholder management abilities.
Mandatory legal work eligibility and physical residency with a preference for local candidates in the PST time zone.

Nice-to-Have Skills

Professional certifications such as Databricks Certified Data Engineer Associate/Professional or AWS Certified Data Analytics.
Prior professional working experience in top‑tier technology consulting firms, SaaS companies, or enterprise data organizations.
Hands‑on familiarity with modern data stack orchestration tools (Apache Airflow, dbt, Prefect) and containerization (Docker, Kubernetes).
Experience integrating enterprise data warehouses (Snowflake, Redshift, BigQuery) into centralized analytics platforms.
Exposure to streaming data architectures (Kafka, Kinesis) and machine learning feature engineering pipelines.

Application Information

Salary/Rate: Market Competitive / Enterprise Data Package
Deadline: Open until filled (Urgent Remote Data Engineer Opening)
Notice Period: Immediate to 30 Days Preferred
Contract Duration: Permanent / Full-Time Remote Engagement (PST Zone Preference)
Company Website:

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Common Interview Questions And Answers

1. HOW DO YOU PLAN YOUR DAY?

This is what this question poses: When do you focus and start working seriously? What are the hours you work optimally? Are you a night owl? A morning bird? Remote teams can be made up of people working on different shifts and around the world, so you won't necessarily be stuck in the 9-5 schedule if it's not for you...

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This is a great question because it shows your comfort level with technology, which is very important for a remote worker because you will be working with technology over time...