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Strong brand, metro location, mid-level experience, and common data-engineer title increase candidate competition.
Role demands big-data and streaming expertise, so skills are transferable across companies but remain domain-specialized.
Explicit years plus multiple mandatory big-data and streaming technology requirements make shortlisting highly strict.
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Oversee and mentor a data engineering team to achieve individual and organizational goals, ensuring project progress and alignment.
Design, build, and optimize scalable data pipelines and systems using Big Data technologies (e.g., Kafka, Spark, Delta lake) for high-volume data processing.
Collaborate with sales and engineering teams to deliver accessible data insights that drive organizational performance improvements.
Bachelor's or Master's degree in Computer Science.
1 to 3 years of professional experience in Big Data engineering roles.
At least 1 year experience with Big Data tools such as Kafka, Apache Spark/EMR, Hive/Impala, Delta lake, Presto, and Airflow, including performance tuning at terabyte scale.
Proficient in programming languages such as Java, Scala or Python.
Experienced in managing and mentoring junior engineers within data-focused teams with focus on project ownership and progress tracking.
Proficient in building streaming data solutions using Apache Flink, Spark Streaming, or Samza and working knowledge of AWS Big Data ecosystem.
Able to integrate and collaborate across sales and engineering functions to ensure data solutions meet business needs and optimize performance.