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Specialized big-data stack and lesser-known brand reduce applicant competition.
Data engineering skills are broadly transferable across industries despite a preferred fintech domain background.
Multiple mandatory big-data technologies, SQL expertise, and core programming requirements create strict shortlisting filters.
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Design, build, and maintain scalable data pipelines using Hadoop, Spark, Snowflake, and Kafka to support large-scale and real-time data processing.
Optimize complex SQL queries for relational and NoSQL databases like PostgreSQL, Oracle, and Cosmos DB to ensure performance and scalability.
Develop high-performance data solutions leveraging programming skills in Python and/or Java integrating with cloud platform APIs.
Expert-level proficiency in SQL with experience in both relational (PostgreSQL, Oracle) and NoSQL (Cosmos DB) databases.
Strong programming skills in Python and/or Java with object-oriented programming experience.
Experience in building and optimizing big data pipelines using technologies such as Hadoop, Spark, Snowflake, and Kafka.
Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline. Work Experience Required: Not explicitly mentioned in the JD.
Has hands-on experience with real-time stream processing technologies like Spark Streaming and Kafka Streams.
Familiarity with cloud platforms (AWS, Azure, GCP) and related certifications enhance fit for role.
Comfortable working in fintech or financial services domain and skilled in DevOps practices including CI/CD pipelines.