Data Engineer (Financial Services)

Lead Data Systems Engineer - Cybersecurity (Data Engineering Focus)Location: Plano, TX (Hybrid - 3 days onsite)Duration: 12 months (long-term program)Interview: Single stage (Technical + Behavioural)We're supporting a major Financial Services organisation building out its Cybersecurity Data Platform, a critical function responsible for detecting, analysing, and preventing large-scale digital threats.This is not a standard Data Engineering role. You will operate at the intersection of high-volume data processing and machine learning, building the core infrastructure that enables real-time threat detection.The role is weighted 80 percent towards Data Engineering and 20 percent towards Machine Learning integration. It is suited to someone who is strong on fundamentals and experienced in moving and processing large-scale data within high-throughput environments. What You'll Be DoingDesigning and building production-grade data pipelines for high-volume security telemetryDeveloping near real-time ingestion frameworks using DatabricksTransforming raw data into ML-ready datasets for threat detection modelsWorking closely with ML teams to support GenAI-driven security use casesOptimising pipelines for performance, scalability, and reliabilityHandling both structured and semi-structured data at scaleWhat We're Looking ForSenior Data Engineering experience in large-scale environmentsStrong Python expertise (Pandas / DataFrames)Deep experience with PySpark / Apache SparkHands-on experience with Databricks + AWS (S3, Glue, EMR, Lambda)Proven track record working with high-throughput streaming (Kafka)Strong understanding of data modelling (SCD, pipeline automation, scalable design)Experience building pipelines beyond basic batch processing - true real-time or near real-time systemsDarwin Recruitment is acting as an Employment Business in relation to this vacancy.