Big Data ML Engineer

Job Description: Design, build, and operate large-scale batch and real-time data pipelines that move, transform, and publish data across the enterprise with high reliability and low latency

Collaborate with Agile teams to architect end-to-end data solutions - from ingestion and orchestration through to event streaming and downstream delivery

4+ years of experience building or operating data pipeline and orchestration systems

4+ years of data or application engineering experience, including Java, Python and SQL

4+ years of experience building and operating real-time or event-driven data systems

4+ years of experience with distributed data and computing tools (Kafka, Spark, EMR, Hadoop, or equivalent)

4+ years of experience with cloud data warehousing platforms at scale

4+ years of experience with cloud platforms (AWS, Azure, or GCP)

3+ years of experience with pipeline scheduling and workflow orchestration tools

2+ years of experience with secure secrets management and credential handling in production systems

2+ years of experience working in Agile engineering environments

Familiarity with data observability practices - monitoring, alerting, SLA tracking, and data quality frameworks Experience in financial services or other regulated, compliance-driven industries