Position Title : Lead Data & Analytics Engineer – Financial Systems

Overview:

We are seeking a highly skilled Lead Data & Analytics Engineer with strong expertise in end-to-end data processing systems and financial data analytics. The role requires not only deep technical knowledge across data lakes, ETL, and analytics platforms but also proven experience leading teams and delivering enterprise-grade IT and dashboarding solutions.

Key Responsibilities:

  • Data Systems Architecture & Engineering
    • Design, build, and optimize large-scale ETL pipelines and data processing systems across platforms such as Azure, AWS, ClickHouse, and Apache Iceberg.
    • Ensure data quality, governance, lineage, and security across ingestion, storage, and consumption layers.
  • Financial Data Analytics
    • Analyze and model transaction processing systems (e.g., ISO 8583) to detect anomalies, risks, and inefficiencies.
    • Implement and enhance anti-money laundering (AML) solutions, fraud detection models, risk scoring, and cash flow analytics.
    • Work closely with business stakeholders to translate financial compliance and regulatory needs into data-driven insights.
  • Full-Stack IT & Dashboarding
    • Oversee and manage end-to-end IT systems supporting data pipelines, APIs, and analytical workloads.
    • Develop and manage dashboards, reporting tools, and visualization platforms to deliver actionable insights to business users and executives.
    • Ensure performance, scalability, and reliability of analytics platforms.
  • Leadership & Collaboration
    • Lead, mentor, and grow a team of data engineers, analysts, and developers.
    • Collaborate with cross-functional teams including finance, compliance, product, and IT infrastructure.
    • Drive best practices in agile delivery, DevOps, CI/CD, and cloud-native architectures.

Required Qualifications :

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Finance Technology, or related field.
  • 8+ years of experience in data engineering/analytics with at least 3+ years in a leadership role.
  • Strong hands-on expertise with cloud platforms (Azure, AWS), data lakes/warehouses (ClickHouse, Iceberg, Delta Lake, etc.), and ETL frameworks.
  • Solid understanding of financial systems (ISO 8583 transactions, AML, fraud analytics, risk scoring).
  • Experience with dashboarding/BI tools (e.g., Superset, Power BI, Tableau, Grafana).
  • Proven ability to lead cross-functional teams and deliver complex projects at scale.

Preferred Skills :

  • Knowledge of streaming platforms (Kafka, Event Hub, Flink).
  • Familiarity with machine learning for fraud/risk detection.
  • Experience with regulatory compliance systems in finance.
  • Strong communication skills with the ability to bridge technical and business domains.

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