Senior Data Engineer

1 week ago

Karachi, Sindh, Pakistan Logiciel Services Full time 120,000 - 240,000 per year

Qualification:

  • Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field Master's preferred .
  • 3–5 years of experience in data engineering, with proven expertise in governance frameworks, metadata management, and knowledge graph / ontologies .
  • Demonstrated experience with tools/platforms such as Apache Atlas, Neo4j, Spark, Kafka, and cloud-based data lakes AWS, Azure, or GCP

Experience:

  • Deep understanding of data governance principles e.g., integrity, compliance, security .
  • Experience with ontology modeling languages e.g., OWL, RDF and knowledge graph tools e.g., Stardog, GraphDB .
  • Familiarity with financial domain standards e.g., FIX protocol, ISO 20022 and regulatory requirements e.g., Basel III, SEC rules .
  • Proficiency in programming languages Python, Java, Scala and big data technologies Hadoop, Hive, Flink .

Job Description:

Role:

As a Senior Data Engineer, you will design, implement, and govern data pipelines and frameworks that power our UHFT operations. You will ensure data integrity, compliance, and availability while building scalable solutions for master data, reference data, and metadata management. This role requires expertise in data governance, knowledge graph construction, and ontology design to support real-time analytics and regulatory adherence .

Responsibilties:

  • Data Governance & Compliance: Develop and enforce governance frameworks aligned with industry best practices e.g., data quality, accountability, transparency and regulations e.g., GDPR, MiFID II .
  • Master & Metadata Management: Architect systems for managing master data, reference data, and metadata, ensuring consistency, accuracy, and traceability across distributed systems .
  • Knowledge Graphs & Ontologies: Design domain-specific ontologies and build knowledge graphs to model relationships between financial instruments, markets, and transactions, enabling semantic interoperability .
  • Data Security & Privacy: Implement robust security protocols e.g., encryption, access controls and ensure compliance with data privacy standards .
  • Performance Optimization: Collaborate with cross-functional teams to reduce latency in data pipelines and improve system scalability for real-time trading workloads .
  • Documentation & Standards: Define governance policies, data dictionaries, and technical documentation to support audit trails and regulatory reporting .

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