Staff Data Reliability Engineer

Jobtailor; Illinois; On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor is seeking a data-focused technologist to own data quality and observability across critical data products. You will work with Data Engineering to embed reliability patterns into pipelines, automate validation, and lead incident response for data issues.

The role requires 5+ years in infrastructure/data environments, hands-on experience with Snowflake and cloud platforms, and strong DataOps practices. Expect collaboration with application teams and enterprise ASP.NET-based solutions.

Qualifications

• Authorized to work in the US without sponsorship.
• No STEM OPT endorsement.
• Bachelor's degree.
• 5+ years’ experience in Infrastructure/Data technology with hands-on responsibilities.
• 3+ years’ experience in Data Engineering, Data Quality, or SRE in an enterprise data environment.
• Hands-on experience with data warehousing and data lake tech including Snowflake and cloud environments (AWS/GCP).
• ETL pipelines using SSIS/SSMS.
• Experience with Informatica, Python/Pyspark, and distributed compute (EMR/Hadoop).
• Designing data quality checks, validation frameworks, and governance standards.
• Hands-on software or cloud engineering experience.
• Familiarity with cloud providers and core compute/containers/databases/APIs.
• Data observability concepts/tools and impact on business outcomes.
• AIOps for monitoring/self-healing data pipelines; ML-based anomaly detection.
• Prompt engineering with AWS or Google AI services.
• DataOps practices implementation.

Responsibilities

• Establish and enforce Data Service Level Objectives for data products.
• Implement advanced data observability tools across the data journey.
• Detect data quality anomalies, schema drifts, and pipeline delays in real time.
• Collaborate with Data Engineering to embed reliability patterns into pipelines.
• Automate data validation, reprocessing, backfilling, and other tasks.
• Lead incident response and resolution for data-related issues.
• Ensure fast recovery and conduct blameless post-incident reviews.
• Develop and automate data-aware runbooks for failures and data recovery.
• Partner with application teams to support software solutions using .NET and ASP.NET.
• Develop and maintain robust enterprise web applications using ASP.NET.

Skills

Data Engineering

Data Quality

DataOps Practices

Advanced Data Observability

AIOps Implementation

Prompt Engineering

Education

Bachelor's degree

Tools

Snowflake

AWS

GCP

EMR

Hadoop

.NET Framework

ASP.NET

SSIS

SSMS

Informatica

Python/Pyspark

Job description

• Establish and enforce Data Service Level Objectives focused on data freshness, completeness, and accuracy across critical data products
• Implement advanced data observability tools across the data journey from ingestion to consumption
• Detect data quality anomalies, schema drifts, and pipeline delays in real time
• Collaborate with Data Engineering to embed reliability patterns into data pipelines
• Automate data validation, reprocessing, backfilling, and other manual operational tasks
• Lead response and resolution for data-related incidents
• Ensure fast recovery and conduct effective blameless post-incident reviews
• Develop and automate data-aware runbooks for data pipeline failures, data quality issues, and data recovery scenarios
• Partner with application teams to support and enhance software solutions utilizing the .NET framework
• Develop and maintain robust enterprise web applications using ASP.NET

Requirements

• Candidates must be authorized to work in the US without company sponsorship
• The company will not support the STEM OPT I-983 Training Plan endorsement for this position
• Bachelors degree
• 5+ years’ overall experience in an Infrastructure, Data or related technology organization with increasing responsibilities as a hands-on technologist
• 3+ years’ experience in Data Engineering, Data Quality, or a specialized SRE role within an enterprise data environment
• Hands-on experience with data warehousing and data lake technologies, including Snowflake, and cloud environments (AWS/GCP)
• Hands-on experience with ETL pipelines using SQL Server Integration Services (SSIS) and SQL Server Management Studio (SSMS)
• Experience in pipeline development and support using Informatica, Python/Pyspark, and distributed compute (EMR/Hadoop)
• Experience designing and implementing data quality checks, data validation frameworks, and data governance standards
• Hands-on experience in software or cloud engineering
• Familiarity with cloud service providers and core capabilities including compute, containers, databases, and APIs
• In-depth hands-on experience with data observability concepts and tools
• Strong understanding of the data journey and impact of data issues on business outcomes
• Expertise implementing AIOps to monitor, manage, and self-heal data pipelines using machine learning principles for anomaly detection
• Experience with prompt engineering and AWS or Google AI services
• Expertise defining and implementing DataOps practices

Core Competencies

Demonstrates expertise in Data Engineering and Data Quality, with a strong focus on implementing DataOps practices and advanced data observability tools. Proficient in developing and maintaining data pipelines, ensuring data accuracy, and automating operational tasks within cloud environments.

Highest-signal resume keywords

• Data Engineering
• Data Quality
• DataOps Practices
• Advanced Data Observability

ATS Optimization Keywords

Hard Skills

• Data Warehousing
• Data Lake Technologies
• SQL Server Integration Services (SSIS)
• SQL Server Management Studio (SSMS)
• Informatica
• Python/Pyspark
• AIOps Implementation
• Data Validation Frameworks
• Machine Learning Principles
• Prompt Engineering

Soft Skills

• Collaboration
• Incident Response
• Problem Solving
• Effective Communication

Industry Keywords

• Data Service Level Objectives
• Data Quality Anomalies
• Schema Drifts
• Data Governance Standards
• Data Journey
• Cloud Service Providers

Tools & Technologies

• Snowflake
• AWS
• GCP
• EMR
• Hadoop
• .NET Framework
• ASP.NET