2204 IT & Software Developer jobs in the US
Requirements
Must:
- 5-7 years of experience in data quality engineering, data observability, or data operations with a focus on platforms
- Practical knowledge of CloudWatch (metrics, logs, alarms, dashboards) and Grafana
- Strong background in implementing data quality frameworks such as Great Expectations, dbt tests, Deequ, or similar
- Familiarity with data lineage and cataloging tools like AWS Glue Catalog, Apache Atlas, DataHub, or equivalent
- Proficiency in SQL and Python for metrics collection, automated reporting, and DQ rule execution
- Experience in developing SLA dashboards and automated reporting for data pipelines
- Understanding of data observability concepts including freshness, volume, schema change detection, and distribution anomalies
- Knowledge of AWS cost monitoring tools such as Cost Explorer, CUR, and CloudWatch billing metrics
- Excellent communication skills for generating reports and presenting SLA performance to stakeholders
- Experience collaborating with data governance teams on data contracts, classification, and quality rules
Responsibilities
- Oversee the monitoring, alerting, lineage, and SLA reporting for all ingestion pipelines
- Implement metrics collection at the pipeline level, including in/out records, processing delays, throughput, failure counts, and data freshness indicators
- Create and sustain monitoring dashboards in CloudWatch and/or Grafana for all operational ingestion pipelines
- Establish alerting thresholds aligned with agreed SLAs, ensuring timely alerts for pipeline delays, failures, and quality breaches
- Document data lineage and metadata for all ingestion pipelines and publish this information to the Boeing Data/Developer Portal or catalog
- Design and enforce data quality rules (such as completeness, schema adherence, record counts, and freshness) in partnership with Data/Cloud Engineers and governance teams
- Generate automated weekly and monthly SLA reports detailing ingestion success rates, data freshness, incident counts, and trend analysis
- Develop cost monitoring views for ingestion compute expenses and provide recommendations for optimization
- Collaborate with Boeings monitoring and observability teams for dashboard and alert integration
- Assist in incident assessment by offering pipeline health diagnostics and root cause analysis
- Continuously update and develop DQ and observability standards as new data sources are integrated each month
Description
At our company, we are dedicated to innovation in the aerospace industry, providing cutting-edge solutions and services. We offer a dynamic work environment in Seattle, WA, promoting a hybrid model that requires onsite presence 2-3 days per week. We are seeking experienced candidates with over 7 years of expertise to join our team as Data Quality/Observability Engineers. Our team emphasizes collaboration, technical excellence, and ongoing learning, ensuring that we remain at the forefront of our field while delivering exceptional value to our clients.
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You can find Data Engineer salaries in the United States here.
How many Data Engineer jobs are in the United States?
Currently, there are 2204 Data openings. Check also: Spark jobs, Snowflake jobs, Kafka jobs, Hadoop jobs - all with salary brackets.
Is the US a good place for Data Engineers?
The US is one of the best countries to work as a Data Engineer. It has a vibrant startup community, growing tech hubs and, most important: lots of interesting jobs for people who work in tech.
Which companies are hiring for Data Engineer jobs in the United States?
KUBRA, Nurse Next Door, Snaplii, Gatestone & Co. Inc, Helm Operations Software inc, Agilus, Cluster Systems among others, are currently hiring for Data roles in the United States.
The company with most openings is Jobot as they are hiring for 126 different Data Engineer jobs in the United States. They are probably quite committed to find good Data Engineers.
The company with most openings is Jobot as they are hiring for 126 different Data Engineer jobs in the United States. They are probably quite committed to find good Data Engineers.
