Data Engineer with Flink

Overview

On Site

$55 - $60

Accepts corp to corp applications

Contract - Independent

Contract - W2

Contract - 12 Month(s)

Skills

Data Engineer

Flink

Scala

AWS

Job Details

Job Title: Flink Data Engineer

Location: Mountain View, CA (100% Onsite from Day 1)

Job Description

We are seeking a highly skilled Flink Data Engineer to join our team in Mountain View, CA. The ideal candidate will have deep expertise in building large-scale data processing systems with Apache Flink, Spark, and AWS technologies. You will work closely with cross-functional teams to design, develop, and maintain real-time and batch data pipelines that support business-critical applications.

Responsibilities

Design and develop scalable data pipelines using Apache Flink, Apache Spark, and Scala.
Build and maintain data integration solutions across diverse data sources using AWS services.
Develop efficient, reusable, and reliable code in Java and Scala.
Implement both real-time stream processing and batch processing architectures.
Collaborate with data scientists, architects, and engineering teams to deliver end-to-end data solutions.
Monitor, tune, and optimize performance of data workflows and job executions.
Ensure data quality, security, and compliance across the data lifecycle.
Troubleshoot and resolve data-related technical issues in production and non-production environments.

Required Skills & Qualifications

5+ years of experience in data engineering or backend software development.
Strong programming proficiency in Java and Scala.
Hands-on experience with Apache Spark and Apache Flink for both batch and stream processing.
Solid experience with AWS services such as S3, EMR, Lambda, Kinesis, Glue, and Redshift.
Strong understanding of distributed systems and cloud-native design patterns.
Experience in designing data models and working with large-scale datasets.
Familiarity with CI/CD pipelines and tools such as Git, Jenkins, etc.

Preferred Qualifications

Experience with containerization tools such as Docker and orchestration using Kubernetes.
Understanding of data lake architectures and the modern data stack.
Knowledge of SQL and NoSQL databases.
Experience with monitoring and logging tools such as Prometheus, Grafana, or CloudWatch.

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