- Individuals within the Data Engineering role work closely with business stakeholders and EITS team members to understand the business requirements that drive the analysis and design of quality data solutions.
- These solutions must be aligned with business and IT strategies and in compliance with the organization s architectural standards.
- Data Engineers are involved in the full systems life cycle and therefore responsible for designing, coding, testing, implementing and supporting data platforms and processes that are delivered on time and within budget.
- Participation in component and interface design, technology planning, product evaluation, advanced testing processes and buy vs. Build recommendations.
- Individuals also provide input to project plans related to their responsibilities.
- They ensure data availability, integrity and compliance by performing data cleansing and data validations.
- They provide data that is congruent, synchronized and reliable, and facilitate user access to data in a semantically meaningful way.
- They analyze and develop logical and physical data models; data sourcing, transformation and aggregation logic; and semantic data access layers in support of corporate, customer and/or business partner business analytics requirements.
- They maintain data catalogues and metadata to facilitate self-service access by business users, other data engineers, data visualization specialists and data scientists.
- When data related system problems occur, they also perform root-cause analysis and recommend or execute corrective action.
- Data Engineers understand the methodologies and technologies that manage the flow of data within and between technology systems and business functions/operations.
- They identify opportunities to reduce data redundancy, improve efficiencies and enhance business value, and monitor trends in data uses.
Primary Responsibilities and Activities:
- Conceptualize, design and develop data integration, transformation and analytics solutions that provide semantically meaningful information to consumers, including internal and external business stakeholders, data visualization specialists and data scientists.
- Working with source data system owners, in most cases our EITS Delivery Management team, determine how to best source data for business analytics, considering current and future needs, infrastructure and security requirements, load frequencies, etc.
- Working with business stakeholders, Data Visualization Specialists and/or Data Scientists, determine semantic data access requirements, design/develop data access layers and data transformation and aggregation logic; technologies include RDBMS, Hadoop, Hive, Spark, columnar databases, etc.
- Maintain metadata, data catalogue and data lineage information.
- Collaborate with data engineers and analytics and subject matter experts to identify useful and strategically relevant insights.
- Work closely with business users, vendors and delivery teams to understand the business requirements that drive the analysis and design of business analytics and reporting solutions.
- Knowledge of current and emerging data architecture products, services, platforms and processes is required.
- Individuals in this role understand how information is turned into knowledge and how this knowledge supports and enables key business processes.
- They must have a solid understanding of logical data warehousing design principles and data access requirements for business analytics and exploration.
- Also required are analytical skills.
- The ability to establish and maintain effective working relationships with team members, as well as an innate curiosity around wanting to understand business processes.
- Business strategy and strategic business initiatives to help drive incremental business value from enterprise data assets.
- Show strong team building and creative thinking skills, and a desire to "make a difference."
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