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# Data Base Engineer

- **Company:** Accurate Infrastructure Data, Inc.
- **Location:** Chicago, United States
- **Experience:** Expert
- **Salary:** $154,000.0 - $170,000.0
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Big Data, BigTable, BigQuery, Ubuntu (Operating System), Databases, Information Engineering, Data Governance, Data Integrity, Data Security, Shard (Database Architecture), Linux, Ganglia (Software), Apache Hadoop, Apache Hive, Nagios, Performance Tuning, Red Hat Enterprise Linux, Redis, Cloudera, Sqoop, Teradata SQL, Backup and Restore, Transport Layer Security, Data Storage Technologies, System Availability, Grafana, Apache Spark, Infrastructure Automation Frameworks, Information Technology, Data Management, Kibana, Data Pipelines
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/senior-data-base-engineer-groupon-company-8328721

## About the Role

* Bachelor's degree in Computer Science or related field or foreign equivalent degree plus 5 years of related experience
 * Any level of experience with Develop and maintain big data infrastructure using Hadoop ecosystems such as Cloudera distribution, ensuring effective data storage and processing with Hive, Spark, and Sqoop
 * Any level of experience with Configure and optimize servers running on Linux-based operating systems, such as RHEL and Ubuntu, to ensure high availability and optimal system performance
 * Any level of experience with Oversee Redis database administration, including sharding, cluster setup, scaling, rebalancing, and implementing SSL for data security
 * Any level of experience with Monitor and troubleshoot systems using tools like Kibana, Grafana, Nagios, and Ganglia to ensure infrastructure reliability and scalability.

## Description

* You will Deploy, configure, and manage a variety of applications, databases, and big data platforms (e.g., BigQuery, Bigtable, Hadoop, Google Dataproc, Redis, Teradata, Keboola), ensuring high availability, performance, and scalability.
 * Monitor system health, troubleshoot issues, automate operational tasks, manage user access, and implement backup and recovery strategies;
 * Partner with data engineering and analytics teams to gather requirements, design data schemas, and support data pipeline development.
 * Enable infrastructure provisioning to support scalable data pipelines and analytics solutions.
 * Provide guidance on efficient resource usage and cost management
 * Optimize system performance and costs across data platforms while enforcing data governance, security policies, and data integrity standards
 * Develop and maintain automation scripts for provisioning, monitoring, and alerting., Extreme Ownership: If a downstream application breaks because of a schema decision, you own the diagnosis. You don't stop at
the database boundary.

Impact Obsessed: Clean design that nobody uses doesn't count. Your deliverables exist to make applications faster, data more
reliable, and teams more independent.

Speed Over Comfort: Imperfect data models that are documented and iterable beat perfect ones that never ship.


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