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Senior niche big-data skillset at a less-known employer reduces applicant density.
Data engineering skills transfer across industries but require specific platform and tooling experience.
Specific big-data tech stack and senior data-engineering expectations enforce strict technical filters.
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Design, build, and maintain scalable big data pipelines using technologies such as Hadoop, Spark, Snowflake, and Kafka.
Optimize query performance and data workflows in production environments for large-scale and real-time processing.
Develop efficient data solutions leveraging advanced SQL, database expertise, and programming in Python and/or Java.
Expert-level proficiency in SQL with hands-on experience in relational (PostgreSQL, Oracle) and NoSQL (Cosmos DB) databases.
Strong programming skills in Python and/or Java with object-oriented programming experience.
Experience developing big data pipelines using technologies like Hadoop, Spark, Snowflake, or Kafka.
Degree in Computer Science, Engineering, or related field preferred but not explicitly mandatory; Work Experience Required: Not explicitly mentioned in the JD.
Experienced in designing and optimizing complex data pipelines suitable for large-scale and real-time data processing environments.
Familiar with cloud platforms and integration through APIs; experience with stream processing and DevOps practices is a plus.
Has domain knowledge in financial services or fintech and comfortable communicating technical concepts across diverse business and leadership audiences.