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Metro locations and a popular data-engineer title at a known bank increase candidate density.
Core data-engineering skills are transferable, though banking compliance and domain knowledge increase specificity.
Explicit 12+ years and extensive mandatory tech stack make filters highly restrictive.
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Design, build, and maintain scalable data pipelines, ETL processes, and data architectures including data lakes and warehouses.
Develop and support real-time data streaming applications using Apache Spark Streaming and Apache Flink, including performance tuning for large-scale data processing.
Ensure data quality, integrity, security, and compliance across data platforms while mentoring junior engineers and collaborating cross-functionally.
At least 12 years of professional experience as a Data Engineer or similar role.
Strong expertise in Apache Spark (including Spark Streaming), Apache Flink, Scala, Python, and experience with AWS services like EMR, Kinesis, DynamoDB, Athena, and QuickSight.
Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field.
Experience with ETL tools and frameworks, data pipeline orchestration, data modelling, schema design, data security standards (including GDPR compliance), and containerization (Docker, Podman).
Senior-level data engineer experienced in large-scale, real-time data streaming and performance optimization using Spark and Flink in cloud environments.
Proficient with advanced data architectures, AI integration in data workflows, and building high-performance data APIs, demonstrating strategic technical leadership.
Experienced in cross-functional collaboration and mentoring, with expertise in data governance, DevOps/CI-CD practices, and compliance with data privacy regulations.