Data Engineer

Key Accountabilities and main responsibilities

Strategic Focus

• Contribute to the development of the data engineering capability.
• Apply software engineering best practices and database design to build scalable data pipelines, data integrations, and data models for use in applications and reports.
• Transform raw data into clean, accurate, and reusable datasets with combination of technical expertise and business acumen to seamlessly integrate data thus facilitating data-driven decision-making throughout the organization.
• Responsible for data curation - translating data needs from stakeholders into architecting, building, and maintaining efficient & reliable data models and pipelines.
• Determining business needs and drivers through stakeholder consultation and collaboration and translate them into actionable requirements for data products.
• Keep up to date with latest trends and best practices in data technology.

Operational Management

• Design, develop, and implement data solutions using our MS stack tools.
• Executing against the Data and Analytics roadmap, including optimisation of the existing capability as we'll as introduction of new data capabilities.
• Utilize data modeling techniques, to structure data for efficient analysis.
• Apply various transformations to ensure data accuracy, including removing inaccuracies or corrupted data and aggregating data items.
• Maintain comprehensive data documentation to ensure a common understanding of data definitions and language across the team.
• Apply standard practices, including version control, unit testing, and continuous integration.
• Collaborate with stakeholders and cross-functional teams to identify business opportunities and enhance strategies with automated data solutions.
• Partner closely with other engineers and analysts to improve foundational data models and accelerate the productization of data insight.

Governance & Risk

• Ensure timely completion of activities by adhering with the agreed processes & quality standards.
• Individual should adhere to data design best practices.
• Adhere to MUFG s standards, policies, and procedures.
• The above list of key accountabilities is not an exhaustive list and may change from time-to-time based on business needs.

Experience & Personal Attributes

Experience

• Overall, 7-10 years of development experience with advanced SQL skills with the ability to develop efficient queries of varying complexity.
• Minimum 3-5 years of data engineering experienced in SQL database development and end-to-end ETL processes.
• Experience working with SSIS and other data transformation tools.
• Expertise to Implementing Data Warehousing Solutions.
• Developing Modern Data Warehouse solutions using Azure Stack (Azure Data Lake, Azure Data Factory, Azure Databricks).
• Excellent Understanding of Modern Data Warehouse/Lambda Architecture, Data warehousing concepts.
• Proficient in a source code control system such as GIT; Strong T-SQL scripting and data modelling skills.
• Coding Spark Scala or Python is desirable.
• Strong relational and dimensional Data Modelling skills is desirable.

Personal Attributes

• Effective verbal and written communication skills, needed to communicate with global teams/stakeholders.
• Practical and simple problem-solving approach.
• Effective Team player with collaborative skills, learning and proactive attitude.
• Quality orientation with attention to detail.
• Commitment to continuous improvement.
• Excellent planning and organizational skills.
• Collaborate and share knowledge with other members of the team to ensure we are always evolving our collective skills and staying on the cutting-edge.
• Effectively communicate complex technical concepts to non-technical stakeholders and collaborate closely to understand evolving business requirements.