• A cloud observability engineer’s day is about making complex systems understandable, improving signal quality, and enabling faster, smarter debugging across teams. • Check system health, review alerts/incidents. • Triage alerts • Investigate issues • Improve observability instrumentation • Build and improve dashboards • Alert optimization • Work with development teams and other engineering partners. • Continuous improvements. • Release support. • Design and implement observability frameworks using metrics, logs, and distributed tracing • Develop dashboards, alerts, and visualizations to monitor system health • Standardize observability practices across engineering teams (logging, telemetry, tracing) • Implement and manage native monitoring tools. • Build alerting systems (avoid alert fatigue) • Participate in on-call rotations • Build intelligent alerting using Improve System Reliability/ proactively reduce risk • Identify reliability risks to help harden systems against failure • Reduction in alert noise / false positives • Increased observability coverage (% of services instrumented) • Improved SLO compliance • Embed observability into applications • Add tracing/metrics into code • Standardize logging formats • Ensure all services are observable end-to-end

• Lead development of data solutions, pipelines, and API-driven database components • Drive high‑volume data processing and enterprise data architecture efforts

• You will be a part of the team accountable for design, model and development of whole AWS data ecosystem for one of our Client’s. • Involvement throughout the whole process starting with the gathering, analyzing, modelling, and documenting business/technical requirements will be needed. The role will include direct contact with clients. • Modelling the data from various sources and technologies. Troubleshooting and supporting the most complex and high impact problems, to deliver new features and functionalities. • Designing and optimizing data storage architectures, including data lakes, data warehouses, or distributed file systems. Implementing techniques like partitioning, compression, or indexing to optimize data storage and retrieval. Identifying and resolving bottlenecks, tuning queries, and implementing caching strategies to enhance data retrieval speed and overall system efficiency. • Identifying and resolving issues related to data processing, storage, or infrastructure. Monitoring system performance, identifying anomalies, and conducting root cause analysis to ensure smooth and uninterrupted data operations. • Train and mentor less experienced data engineers, providing guidance and knowledge transfer.

Role Description Looking for a Senior Azure & Data Factory Developer for a permanent role by way of 6 month contract-to-hire. This requires a powerhouse SQL/ADF expert who brings sharp thinking, high energy, and enterprise‑grade data engineering to every project. - Lead development of data solutions, pipelines, and API-driven database components - Drive high‑volume data processing and enterprise data architecture efforts Qualifications - 5+ years hands-on SQL development with stored procedures and large‑scale batch processing - Proven experience designing and delivering enterprise data platforms - Building and maintaining Azure Data Factory pipelines - Creating and deploying database‑hosted APIs - Data analysis, transformation, and ETL expertise Requirements - Broader experience across cloud data ecosystems - Additional exposure to advanced data modeling or automation tooling - Familiarity with modern data integration patterns Benefits - Duration: 6 month contract to hire - Pay rate: $55-60/hour on W2 - Salary upon conversion is $115,000 - 100% remote, EST or CST hours