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Popular Data Engineer title and metro hiring increase competition, but niche streaming skills moderate it.
Specialized streaming and Hadoop skills moderately restrict cross-industry transferability.
Explicit 8+ years plus mandatory streaming, Hadoop, Scala/Python, and client-facing experience increases filter strictness.
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Design and implement low latency, high throughput streaming data pipelines using Kafka, Flink, and Spark Streaming.
Build and maintain event-driven architectures for real-time data ingestion and processing, including stateful and stateless stream processing applications.
Collaborate with application teams to define integration points and API specifications; report progress and test metrics to stakeholders.
8+ years hands-on experience in data engineering roles.
Strong expertise with streaming pipelines involving Hadoop ecosystem, Kafka, Flink, Spark Streaming, SQL, Scala, and Python.
Experience with Oracle Database, SQL, PL/SQL, and familiarity with CI/CD tools such as Git, Bitbucket, uDeploy, and ServiceNow.
Expertise in Scaled Agile delivery model and agile ceremonies (daily scrums, sprint planning, sprint reviews, sprint demos).
Experienced in client-facing or consulting roles with strong communication skills able to explain complex technical topics to non-technical stakeholders.
Skilled in working in fast-paced environments managing multiple priorities with problem-solving and analytical thinking.
Familiarity or exposure to enterprise-scale data platforms and cloud-based data ecosystems (AWS, Azure, or GCP) is preferred but not mandatory.