This is a lead developer role in a fast-paced technology delivery organization supporting regulatory compliance. This position is part of AML Monitoring Technology team.

Responsibilities

• Developing and supporting scalable, extensible, and highly available data solutions
• Deliver on critical business priorities while ensuring alignment with the wider architectural vision
• Identify and help address potential risks in the data supply chain
• Follow and contribute to technical standards
• Design and develop analytical data models

Required Qualifications & Work Experience

• First Class Degree in Engineering/Technology (4-year graduate course)
• 8+ years’ experience implementing data-intensive solutions using agile methodologies
• Experience of relational databases and using SQL for data querying, transformation and manipulation
• Experience of modelling data for analytical consumers

• Ability to automate and streamline the build, test and deployment of data pipelines
• Experience in cloud native technologies and patterns
• A passion for learning new technologies, and a desire for personal growth, through self-study, formal classes, or on-the-job training
• Excellent communication and problem-solving skills

Technical Skills (Must Have)

• ETL: Hands on experience of building data pipelines. Proficiency in two or more data integration platforms such as Ab Initio, Apache Spark, Talend and Informatica
• Big Data: Experience of ‘big data’ platforms such as Hadoop, Hive or Snowflake for data storage and processing
• Data Warehousing & Database Management: Understanding of Data Warehousing concepts, Relational (Oracle, MSSQL, MySQL) and NoSQL (MongoDB, DynamoDB) database design
• Data Modeling & Design: Good exposure to data modeling techniques; design, optimization and maintenance of data models and data structures
• Languages: Proficient in one or more programming languages commonly used in data engineering such as Python, Java or Scala
• DevOps: Exposure to concepts and enablers - CI/CD platforms, version control, automated quality control management

Technical Skills (Valuable)

• Cloud: Good exposure to public cloud data platforms such as S3, Snowflake, Redshift, Databricks, BigQuery, etc. Demonstratable understanding of underlying architectures and trade-offs
• Data Quality & Controls: Exposure to data validation, cleansing, enrichment and data controls
• Containerization: Fair understanding of containerization platforms like Docker, Kubernetes
• File Formats: Exposure in working on Event/File/Table Formats such as Avro, Parquet, Protobuf, Iceberg, Delta
• Others: Basics of Job scheduler like Autosys. Basics of Entitlement management
• Certification on any of the above topics would be an advantage.

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Job Family Group:

Technology

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Job Family:

Digital Software Engineering

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Time Type:

Full time

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