Data Reliability Engineer
EmpowerAbout the role
Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them.
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We 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.
What You Will Do
Own the reliability and stability of production data pipelines and data platform services
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, SOPs, and operational documentation
Participate in occasional off-hours support for production data systems when required
What You Will Bring
Minimum 5 years of experience working with production data platforms in AWS environments
Prior experience building data pipelines and seeing them through production, including exposure to real-world failures and operational challenges
Strong 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)
Experience handling production incidents and performing root cause analysis
Strong problem-solving mindset and ability to work through ambiguous production issues
What Will Set You Apart
Experience handling real-world data issues such as pipeline delays or failures
Experience with backfills and reprocessing
Experience with late-arriving or incomplete data
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
This job description is not intended to be an exhaustive list of all duties, responsibilities and qualifications of the job. The employer has the right to revise this job description at any time. You will be evaluated in part based on your performance of the responsibilities and/or tasks listed in this job description. You may be required perform other duties that are not included on this job description. The job description is not a contract for employment, and either you or the employer may terminate employment at any tim
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