Lead Data & Analytics Engineer

Overview

Lead Data & Analytics Engineer

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

• Bachelors 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

  .