IT Applications DATAE01137
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Burbank, CA, USA
As a Data Engineer, you will design, develop, test and maintain efficient and sustainable data models to keep data accessible and ready for analysis. Working closely with the Analytics Team, you will engage with business teams to understand requirements, design conceptual, logical and physical data models, and perform root-cause analysis and recommend solutions. This will be a hands on role utilizing Extract, Transfer & Load (ETL) tools to deliver source to target mappings, physical and logical data models and related scripts to automate the data transformation and loading processes
Essential Job Functions:
Knowledge, Skills, & Abilities:
- Work closely with data experts to build and maintain KPI data dictionary, metadata, data standards, and ensure adherence to the Plans Analytics Method and data standards.
- Engage business teams to understand requirements, document them and deliver robust and scalable solutions in the form of data models that can be leveraged for self-service analytics.
- Explore ways of modeling the Plans unstructured voice and text data into frameworks fit for analysis.
- Design conceptual, logical and physical data models, maintain data dictionary and capture metadata.
- Perform gap analysis as needed for purposes of maintaining, continuously enhancing data models and integrating
- KPI’s into the analytics platform as and when new KPI and business metrics are adapted by the organization.
- Work with application development team to deploy analytics data products through such ways as embedding analysis models into business applications and mobile solutions.
- Establish and maintain provenance, integrity and security of data used for self-service reporting, ad-hoc analysis or other levels of analysis.
- Utilize ETL tools and other data pipeline automation techniques to develop and maintain source to target mapping that includes extract requirements, derived field logic, domain values and data lineage.
- Ensure developed data models are easy to use and efficient to access data thus enable transparency of data lineage to business teams and all stakeholders.
- Proficient in leading business and internal team discussions to gather requirements, brain-storm and propose robust and scalable solutions; leverage business partner/unit input to enhance data models.
- Expert knowledge of relational DBMS, specifically Oracle.
- Expert knowledge in areas of advanced data techniques including unstructured and spatial data.
- Customer focus - Gains insight into customer needs; identifies opportunities that benefit the customer; builds and delivers solutions that meet customer expectations; establishes and maintains effective customer relationships.
- Decision quality – Makes sound decisions, even in the absence of complete information; relies on a mixture of analysis, wisdom, experience, and judgment when making decisions; considers all relevant factors and uses appropriate decision-making criteria and principles; recognizes when a quick 80% solution will suffice.
- Communicates effectively – Is effective in a variety of communication settings: one-on-one, small and large groups, or among diverse styles and position levels; attentively listens to others; adjusts to fit the audience and the message; provides timely and helpful information to others across the organization; encourages the open expression of diverse ideas and opinions.
- Ensures accountability – follows through on commitments and makes sure others do the same; acts with a clear sense of ownership; takes personal responsibility for decisions, actions, and failures; establishes clear responsibilities and processes for monitoring work and measuring results; designs feedback loops into work.
- Instills trust – follows through on commitments; is seen as direct and truthful; keeps confidences; practices what he/she preaches; shows consistency between words and actions.
Manages Ambiguity- Operating effectively, even when things are not certain or the way forward is not clear.
Goal Completion: Inspired to perform well by the completion of tasks
Self-Starter: Inspired to perform without outside help
Ability to Make an Impact: Inspired to perform well by the ability to contribute to the success of a project or the organization
Bachelors or better in Computer Science or related field.
Relevant technical languages and tools such as SQL, Python, NoSQL, Airflow, Quartz, ERWIN or equivalent. Preferred qualifications
Developing and maintaining source to target mapping that includes extract requirements, derived field logic, domain values and data lineage.
Creating and maintaining automated data pipelines, data standards, and best practices to maintain integrity and security of the data; ensure adherence to developed standards.
Designing conceptual, logical and physical data models and maintaining data dictionary and capturing metadata.
5 years: Data engineering, data modeling or data architecture experience with a focus on multidimensional data modeling for both structured and unstructured data.
Work experience in the HealthCare industry preferred