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# Log Analytics Engineer

- **Company:** OpenKyber LLC
- **Location:** Alpharetta, GA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Adaptable Database Systems, Agile Methodology, Airflow, Data Analysis, Big Data, BigQuery, Information Systems, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Migration, Data Security, Data Warehousing, Database Queries, Decision Support Systems, Python (Programming Language), Log Analysis, Meta-Data Management, Standard Sql, SQL Databases, Teradata SQL, Web Analytics, Data Processing, Google Cloud, Chatbots, Data Layers, Information Technology, Performance Monitor, Google Bigquery, Looker Analytics, Data Pipelines
- **Published:** October 10, 2026
- **Apply:** https://www.careerjet.com/jobad/us60fb11a0b49c0cae753f7616f6af3906

## About the Role

* Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent experience).
 * 6+ years of experience in Data Engineering, Analytics Engineering, or Business Intelligence.
 * Strong hands-on experience with Google BigQuery ( Required ).
 * Strong hands-on experience with Looker , including LookML and dashboard development ( Required ).
 * Experience building and managing data pipelines using Airflow Composer (Apache Airflow) .
 * Strong SQL skills with experience developing complex queries and optimizing large datasets.
 * Strong Python programming experience for data processing, automation, and ETL development.
 * Experience designing and implementing scalable data models and semantic layers.
 * Experience building reporting and visualization solutions for business stakeholders.
 * Strong understanding of data warehousing concepts, ETL/ELT processes, and data architecture.
 * Excellent analytical, troubleshooting, and problem-solving skills.

Preferred Skills & Experience

 * Experience building a semantic layer from scratch using Looker (highly preferred).
 * Experience supporting chatbot, conversational AI, customer experience, or digital analytics reporting.
 * Experience integrating data from multiple enterprise data sources.
 * Experience with Teradata .
 * Experience working within Google Cloud Platform (Google Cloud Platform).
 * Knowledge of data governance, data quality, and metadata management.
 * Experience working in Agile environments and collaborating with cross-functional teams.

Nice to Have

 * Experience migrating data from Teradata or other enterprise data warehouses to BigQuery.
 * Familiarity with chatbot analytics, conversational data, or customer interaction reporting.
 * Experience optimizing BigQuery performance and cost.
 * Exposure to CI/CD practices for analytics engineering.

Key Must-Have Skills

 * Data Engineering
 * Google BigQuery (Mandatory)
 * Looker / LookML (Mandatory)
 * Airflow Composer / Apache Airflow
 * Python
 * SQL
 * Semantic Layer Development
 * Data Pipelines
 * Dashboard & Reporting Development, Bachelor s degree in computer science or related degree

## Description

* Design, build, and maintain scalable data pipelines using Airflow Composer to ingest, transform, and load data into Google BigQuery .
 * Develop and optimize data models that support enterprise reporting and analytics.
 * Design and implement semantic layers in Looker (LookML) to provide consistent business definitions, reusable metrics, and governed data access.
 * Build and maintain interactive dashboards and reports using Looker to support chatbot analytics and business performance reporting.
 * Collaborate with business stakeholders, data engineers, analysts, and product teams to gather reporting requirements and translate them into scalable data solutions.
 * Integrate data from multiple sources to create clean, reliable datasets for analytics and visualization.
 * Write efficient and optimized SQL queries for large-scale datasets in BigQuery.
 * Develop automation and data processing scripts using Python.
 * Monitor, troubleshoot, and optimize ETL/ELT workflows to ensure data quality and reliability.
 * Support analytics initiatives by delivering trusted datasets, KPIs, and reporting solutions that enable data-driven decision making.