Data Engineer- Offshore in , United States at Energy Jobline ATTB – US | Jobyssey

Job Description

The Senior Data Engineer / Streaming Data Engineer will design, build, and support enterprise-scale streaming and big data pipelines across AWS, Spark, Hadoop, Kafka, and cloud- ingestion platforms. This role is hands-on and production-focused, with responsibility for reliable real-time data movement, ingestion modernization, distributed systems engineering, and scalable data processing in a large enterprise environment.

• Hands-on streaming and real-time data engineering using Kafka, Spark, AWS Kinesis, and cloud- data services.

• Modernization opportunity focused on moving legacy ingestion patterns to scalable AWS- services.

• Production engineering role requiring strong troubleshooting, operational ownership, and distributed systems depth.

• Enterprise-scale environment with complex data warehousing, big data, and cross-platform integration needs.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their , , , , (including ), , and expression, marital status, , ancestry, genetic factors, , , protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: .

Skills and Requirements

• 10+ years of experience in data engineering, software engineering, or related fields.

• Strong expertise with AWS cloud platform services and cloud- data engineering patterns.

• Hands-on experience with Apache Spark using Scala and PySpark for large-scale data processing.

• Deep working knowledge of the Hadoop ecosystem and distributed data processing architectures.

• Strong experience with Kafka and streaming technologies, including real-time data pipeline design and support.

• Hands-on experience with data ingestion platforms such as Flume, AWS Kinesis, Kinesis Firehose, or similar tooling.

• Strong programming experience in Python, Scala, and Java.

• Deep understanding of enterprise data warehousing, big data architectures, distributed systems, and large-scale enterprise operating environments.

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