{"schemaVersion":"jobsearcher.job.v1","id":"2fb49e8dc5ee41712664be5b","url":"https://jobsearcher.com/jobs/2fb49e8dc5ee41712664be5b","canonicalUrl":"https://jobsearcher.com/jobs/2fb49e8dc5ee41712664be5b","title":"Data Engineer","description":"Data Reliability Engineer 6 months (Only USC)Phone and skypeRemote I would prefer candidates do the Ropes.AI assessment before speaking with them to cut down on time. This takes 30 minutes and is on AWS and Python. Let me know if you have any questions.Role OverviewWe are looking for a hands-on Data Reliability Engineer to own the reliability, stability, and operational excellence of our AWS-based data platform.This role is focused on operating, troubleshooting, and improving production data systems, ensuring that data pipelines and analytics platforms are resilient, performant, and meet business-critical SLAs.You will work closely with data and platform engineering teams to diagnose issues, resolve production incidents, and influence better design and operational practices across the data ecosystem.ESSENTIAL FUNCTIONS:· Own the reliability and stability of production data pipelines and data platform services· Define and enforce data SLAs/SLOs for batch/streaming products· Diagnose and resolve data pipeline failures, delays, and data quality issues in production environments· Investigate issues across distributed data systems (e.g., Spark/EMR workloads, ingestion pipelines, warehouse performance)· Lead or support incident response, including triage, mitigation, and long-term resolution· Perform root cause analysis (RCA) and implement durable fixes to prevent recurrence· Define and improve data SLAs (freshness, latency, completeness) and ensure adherence· Design and enhance monitoring, alerting, and observability for data systems· Develop automation and tooling to reduce operational toil and improve system resilience· Contribute to disaster recovery (DR) and resiliency planning, including backup validation and recovery workflows· Partner with engineering teams to improve pipeline design, reliability, and operational readiness· Create and maintain runbooks, Standard Operating Procedures, and operational documentation· Participate in occasional off-hours support for production data systems when requiredQUALIFICATIONS:· Education: Bachelor’s in Computer Science, Information Systems, Data Science, or related.· 5+ years in data engineering/analytics platform roles with 3+ years operating in production Cloud data warehouse (Redshift, Snowflake, etc.)· 3+ year experience building AWS data pipelines and seeing them through production, including exposure to real-world failures and operational challenges· 3+ year experience working with production data platforms in AWS environments focusing on anomaly detection, reconciliation, and end-to-end validation· 3+ year experience with Python and SQL in real data systems· Hands-on experience troubleshooting distributed data processing systems (e.g., Spark/EMR, Redshift, streaming systems)· Proven ability to debug and resolve production issues in data pipelines and data platforms· Experience with AWS data services (such as EMR, Redshift, DynamoDB, S3, or similar)· Proven ability in handling production incidents and performing root cause analysis· Strong problem-solving mindset and ability to work through ambiguous production issuesPreferred· Experience handling real-world data issues such as pipeline delays or failures· Experience with data backfills and reprocessing· Experience with incoming data late-arrival or incomplete dataset· Experience improving observability and alerting specifically for data systems· Experience influencing or guiding data pipeline reliability and operational practices· Exposure to streaming/event-driven systems (Kafka, Kinesis, CDC patterns)· Experience with disaster recovery, backup validation, and resiliency testing· Strong communication during incidents with both technical and non-technical stakeholders· Prior FinOps or capacity-planning ownership for data platforms.· Familiarity with BI semantic layers and contract enforcement at consumption (Looker/Power BI/Tableau).","company":"Ace Technologies","rawCompany":"ace technologies","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-06-17T05:39:15.536Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer","description":"Data Reliability Engineer 6 months (Only USC)Phone and skypeRemote I would prefer candidates do the Ropes.AI assessment before speaking with them to cut down on time. This takes 30 minutes and is on AWS and Python. Let me know if you have any questions.Role OverviewWe are looking for a hands-on Data Reliability Engineer to own the reliability, stability, and operational excellence of our AWS-based data platform.This role is focused on operating, troubleshooting, and improving production data systems, ensuring that data pipelines and analytics platforms are resilient, performant, and meet business-critical SLAs.You will work closely with data and platform engineering teams to diagnose issues, resolve production incidents, and influence better design and operational practices across the data ecosystem.ESSENTIAL FUNCTIONS:· Own the reliability and stability of production data pipelines and data platform services· Define and enforce data SLAs/SLOs for batch/streaming products· Diagnose and resolve data pipeline failures, delays, and data quality issues in production environments· Investigate issues across distributed data systems (e.g., Spark/EMR workloads, ingestion pipelines, warehouse performance)· Lead or support incident response, including triage, mitigation, and long-term resolution· Perform root cause analysis (RCA) and implement durable fixes to prevent recurrence· Define and improve data SLAs (freshness, latency, completeness) and ensure adherence· Design and enhance monitoring, alerting, and observability for data systems· Develop automation and tooling to reduce operational toil and improve system resilience· Contribute to disaster recovery (DR) and resiliency planning, including backup validation and recovery workflows· Partner with engineering teams to improve pipeline design, reliability, and operational readiness· Create and maintain runbooks, Standard Operating Procedures, and operational documentation· Participate in occasional off-hours support for production data systems when requiredQUALIFICATIONS:· Education: Bachelor’s in Computer Science, Information Systems, Data Science, or related.· 5+ years in data engineering/analytics platform roles with 3+ years operating in production Cloud data warehouse (Redshift, Snowflake, etc.)· 3+ year experience building AWS data pipelines and seeing them through production, including exposure to real-world failures and operational challenges· 3+ year experience working with production data platforms in AWS environments focusing on anomaly detection, reconciliation, and end-to-end validation· 3+ year experience with Python and SQL in real data systems· Hands-on experience troubleshooting distributed data processing systems (e.g., Spark/EMR, Redshift, streaming systems)· Proven ability to debug and resolve production issues in data pipelines and data platforms· Experience with AWS data services (such as EMR, Redshift, DynamoDB, S3, or similar)· Proven ability in handling production incidents and performing root cause analysis· Strong problem-solving mindset and ability to work through ambiguous production issuesPreferred· Experience handling real-world data issues such as pipeline delays or failures· Experience with data backfills and reprocessing· Experience with incoming data late-arrival or incomplete dataset· Experience improving observability and alerting specifically for data systems· Experience influencing or guiding data pipeline reliability and operational practices· Exposure to streaming/event-driven systems (Kafka, Kinesis, CDC patterns)· Experience with disaster recovery, backup validation, and resiliency testing· Strong communication during incidents with both technical and non-technical stakeholders· Prior FinOps or capacity-planning ownership for data platforms.· Familiarity with BI semantic layers and contract enforcement at consumption (Looker/Power BI/Tableau).","datePosted":"2026-06-17T05:39:15.536Z","dateModified":"2026-06-17T05:39:15.536Z","hiringOrganization":{"@type":"Organization","name":"Ace Technologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Denver","addressRegion":"CO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"2fb49e8dc5ee41712664be5b"},"url":"https://jobsearcher.com/jobs/2fb49e8dc5ee41712664be5b"}}