Senior Data Engineer: Real-Time Pipelines & Cloud Analytics

Cloudndata; United States; Hybrid; USD 140,000 - 180,000; Full time

Job summary

Cloudndata is seeking world-class talent to join our data engineering team in the United States. You will design and implement data warehouse architectures, ETL/ELT processes, and analytics tooling across modern cloud environments.

Proficiency in Python, Scala or Java, Spark, Hive, Delta Lake, and Kafka is expected, with strong SQL skills and a passion for scalable, real-time data solutions. This role emphasizes collaboration, innovation, and robust CI/CD practices.

Qualifications

• Bachelor’s degree or higher in a technical field or equivalent education/experience.
• 5+ years in data warehouse architectures, ETL/ELT and analytics tools.
• 3+ years in Big Data stacks (Hadoop, Spark, Hive, Delta Lake).
• 3+ years with multiple file formats and APIs (Parquet, Avro, Delta Lake).
• Experience with AWS cloud environment and serverless tech.
• Strong SQL in relational and NoSQL contexts.
• Proficient in Python, Scala and Java.
• Experience building realtime streaming data pipelines and using Kafka.
• Familiar with CI/CD and GitHub workflows.

Responsibilities

• Build and maintain data pipelines with Lambda/Kappa architecture.
• Develop streaming solutions for real-time analytics.
• Collaborate with teams to solve complex data problems.
• Leverage CI/CD and source control for reliable deployments.

Skills

Big Data

ETL/ELT

Python

Scala

Java

SQL

CI/CD

GitHub

Kafka

Streaming pipelines

Lambda/Serverless

Delta Lake

Spark

Hive

NoSQL

AWS

APIs

Data structures & algorithms

Education

Bachelor’s degree in Computer Science or related

Tools

Hadoop

Spark

Hive

Delta Lake

AWS

Kafka

Job description

Cloudndata is seeking world-class talent to join our data engineering team in the United States. You will design and implement data warehouse architectures, ETL/ELT processes, and analytics tooling across modern cloud environments.

Proficiency in Python, Scala or Java, Spark, Hive, Delta Lake, and Kafka is expected, with strong SQL skills and a passion for scalable, real-time data solutions. This role emphasizes collaboration, innovation, and robust CI/CD practices.