Senior Data Engineer

1 day ago

Kolhapur, India Spydra Full time
Position Summary:

We are looking for an experienced Senior Data Engineer to lead the development of advanced systems for observability and AI-driven analytics. The role involves designing data correlation solutions, implementing predictive models for anomaly detection, and creating proactive monitoring frameworks to enhance operational reliability and minimize system failures.

Primary Responsibilities:

Data Correlation and Insight Generation:

  • Develop solutions to correlate data across multiple observability layers
  • Integrate diverse data streams, such as metrics, logs, traces, and code performance, to diagnose root causes effectively.

Anomaly Detection and Prediction:

  • Build and deploy machine learning models to identify and predict anomalies.
  • Provide early failure warnings to prevent outages, empowering operational teams to take preemptive action.

Data Pipeline and Architecture Development:

  • Design and maintain scalable data pipelines to handle large-scale observability datasets (timeseries data).
  • Optimize real-time data processing, storage, and retrieval for performance and efficiency.

Collaboration and Visualization:

  • Partner with cross-functional teams, including DevOps and SRE, to enhance observability practices and predictive capabilities.
  • Create user-friendly dashboards and visual reports for effective communication of insights.

Continuous Optimization:

  • Refine and enhance observability tools and systems for improved precision, speed, and scalability.
  • Stay informed on the latest trends and technologies in data engineering, observability, and machine learning.
Required Expertise:

Core Competencies:

  • Comprehensive understanding of observability tools and frameworks (e.g., Prometheus, Grafana, Splunk, ELK, Datadog).
  • Strong proficiency in analyzing metrics, logs, and traces, particularly timeseries data.

Data Engineering Proficiency:

  • Hands-on experience in developing robust data pipelines and correlation frameworks.
  • Expertise in cloud-native observability platforms and distributed systems.

Machine Learning Skills:

  • Knowledge of building and implementing predictive analytics models for anomaly detection.
  • Familiarity with ML tools and frameworks like TensorFlow, PyTorch, or scikit-learn.

Programming and Cloud Experience:

  • Advanced skills in programming languages such as Python, Java, or Go.
  • Experience working with cloud platforms (AWS, GCP, Azure) and automation technologies.

Collaboration and Communication:

  • Strong problem-solving skills and ability to work across teams.
  • Effective communicator with a knack for presenting technical insights clearly.


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