Senior Data Engineer

Stott and May United State
Remote
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AI Summary

We're hiring a Senior Data Engineer to build and scale large, distributed data pipelines. The focus is on pipeline design, streaming architecture, and high-volume data processing in production. Strong experience as a Data Engineer on large distributed systems is required.

Key Highlights
Building large scale batch and streaming data pipelines
Working heavily with Kafka or similar event streaming platforms
Developing distributed processing with Spark or Flink
Key Responsibilities
Building large scale batch and streaming data pipelines
Working heavily with Kafka or similar event streaming platforms
Developing distributed processing with Spark or Flink
Optimizing throughput, reliability, and data quality
Collaborating with data, analytics, and platform teams
Technical Skills Required
Kafka Spark Flink Python Java SQL
Benefits & Perks
$70-100 per hour
Fully remote
40 hours per week
Nice to Have
Flink
Terraform exposure
Experience supporting downstream analytics or ML

Job Description


We’re working with a digital client hiring a Senior Data Engineer to build and scale large, distributed data pipelines.

This is a pure Data Engineering requirement. It is not a DevOps or platform engineering role. The focus is pipeline design, streaming architecture, and high volume data processing in production.

You’ll join an established team working on real time and batch data systems at scale.

Six month initial contract, strong extension view.

$70-100 per hour depending on experience, 40 hours per week.

W2 or personal LLC only. No C2C.

Fully remote, EST time zone.

What you’ll be doing

• Building large scale batch and streaming data pipelines

• Working heavily with Kafka or similar event streaming platforms

• Developing distributed processing with Spark or Flink

• Optimizing throughput, reliability, and data quality

• Collaborating with data, analytics, and platform teams

What we’re looking for

• Strong experience as a Data Engineer on large distributed systems

• Kafka in production environments

• Spark or similar distributed processing frameworks

• Strong Python or Java, solid SQL

• Cloud experience preferred, but we are open to engineers from GCP, Azure, or on prem backgrounds

Nice to have

• Flink

• Terraform exposure

• Experience supporting downstream analytics or ML

High scale data engineering. Modern cloud stack. Extensions likely.


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