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Data Engineer – Observability & Insights Platform

5 years

0 Lacs

Posted:3 days ago| Platform: Linkedin logo

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Remote

Job Type

Contractual

Job Description

Job Title: Data Engineer – Observability & Insights Platform

Location: Remote

Employment Type: Contract

Experience: 5+ Years


Key Responsibilities:

1. Observability Signal Correlation

Integrate and analyze signals from logs, metrics, and traces using Grafana and Prometheus

Enrich observability data by correlating it with business context to enable meaningful insights

2. Data Enrichment & Pipeline Development

Build and maintain data pipelines to enhance technical signals with business metadata

Leverage OpenTelemetry (OTel) for observability instrumentation across systems

3. Machine Learning Integration

Design, build, and deploy ML models for anomaly detection, forecasting, and incident noise reduction

Continuously improve ML solutions to increase relevance and business value of incident signals

4. Disruption Prediction & Risk Mitigation

Identify trends and patterns that can predict business disruptions and support preemptive actions

5. Action Enablement

Make observability insights actionable for business stakeholders through accessible dashboards and tools

Support both automated and manual decision-making processes

6. Cross-Functional Collaboration

Work closely with IT, DevOps, and Business teams to ensure alignment between technical implementations and business objectives

7. Continuous Improvement

Monitor and optimize data pipelines for accuracy, reliability, and performance



Required Skills & Qualifications:

Proven experience as a Data Engineer or in a similar role focused on observability and analytics

Strong proficiency in SQL and Python

Experience working on Google Cloud Platform (GCP)

Expertise in BigQuery for business intelligence and analytics

Hands-on knowledge of Grafana, Prometheus, and Splunk as monitoring/observability tools

Familiarity with OpenTelemetry (OTel) for observability instrumentation

Experience with big data technologies such as Apache Spark, Kafka, and Airflow

Machine Learning & Analytical Expertise:

Practical experience applying ML techniques to observability data for anomaly detection and forecasting

Ability to reduce noise in incident alerts and deliver more relevant and high-value insights

Strong analytical mindset to interpret complex datasets and identify actionable trends

Soft Skills:

Excellent communication and collaboration skills to work across technical and business stakeholders

Strong problem-solving abilities and a passion for using data to address real business challenges.

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