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Home
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Snow Planet
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Staff Software Engineer

Staff Software Engineer

Snow Planet

10 - 15 years

40 - 45 Lacs

hyderabad

Posted:6 hours ago| Platform:

Apply

Skills Required

performance tuning automation data management architecture schema data processing data quality analytics downstream python

Work Mode

Work from Office

Job Type

Full Time

Job Description

We are seeking a highly skilled

Staff Engineer with strong expertise in Cribl Pipelines and data streaming

to lead the design, development, and optimization of our observability and data engineering workflows. The ideal candidate will bring hands-on experience with

Cribl Stream/Edge

, advanced

ETL practices

real-time streaming frameworks (Spark, Flink, Kafka)

, and deep knowledge of

observability platforms (Splunk, Prometheus, Grafana, TSDBs)

. This role is both technical and strategic, requiring deep problem-solving skills, architectural vision, and the ability to mentor and guide engineering teams.

What you get to do in this role:

Cribl Pipelines
: Architect and optimize large-scale data pipelines using
Cribl Stream and Cribl Edge
for ingestion, transformation, and routing.
Streaming & Real-Time Processing
: Design and implement
real-time data pipelines
using
Apache Spark, Apache Flink, and Kafka Streaming
to handle high-throughput, low-latency observability data.
ETL/Data Engineering
: Apply advanced ETL practices to cleanse, enrich, filter, and normalize diverse data sources before downstream ingestion.
Observability Data Management
: Manage high-volume telemetry data (logs, metrics, traces, events) and design strategies for
noise reduction, performance optimization, and cost control
.
Integration
: Build robust integrations with
Splunk, Elasticsearch, Kafka, S3, Prometheus, VictoriaMetrics, InfluxDB, and other TSDBs
.
Scalability & Performance Tuning
: Ensure Cribl and streaming pipelines perform reliably at scale, handling
high-cardinality and high-throughput datasets
.
Best Practices & Governance
: Define and enforce observability ingestion best practices, schema governance, and data quality standards.
Leadership & Mentorship
: Guide engineers in
pipeline design, streaming technologies, and observability best practices
.
Innovation
: Explore emerging technologies in observability, streaming, and AI-driven analytics to continuously improve architecture.

To be successful in this role you have:

Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AIs potential impact on the function or industry.
10+ years of software/data engineering experience
, with at least
5+ years hands-on in Cribl (Stream/Edge)
.
Strong background in
ETL pipelines, real-time streaming, and distributed data processing
.
Hands-on expertise with
Apache Spark (Structured Streaming), Apache Flink, and Kafka Streaming
.
Deep understanding of
observability data (logs, metrics, traces)
and platforms such as
Splunk, Elastic, Prometheus, Grafana, OpenTelemetry
.
Experience with
Time Series Databases (TSDBs)
such as
VictoriaMetrics, InfluxDB, TimescaleDB, or ClickHouse
.
Proficiency in
scripting/programming (Python, Go, or Java)
for pipeline extensions and automation.
Strong knowledge of
Kafka, S3, cloud-native services (AWS/GCP/Azure)
for data transport and storage.
Experience with
scalability, performance tuning, and cost optimization
in observability pipelines.
Strong collaboration and leadership skills to
influence cross-functional teams
.
Exposure to
AI/ML-based anomaly detection or predictive observability use cases
.

Staff/Principal Engineer experience

in large-scale data systems.

FD21

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