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Senior Data Engineer

Location: Anaheim, CA
The Data Engineer III will collect and curate data from disparate sources to perform data interrogation, develop analytical and predictive analytic solutions, and deep data modeling Research and Development to provide actionable insights.   The Data Engineer III is expected to clean, prepare, and optimize data for consumption.  Strong technical and analytical skills are required to construct data sets that can provide actionable insights.  The Data Engineer III will apply complex tools and algorithms to identify trends and patterns in data. 

The Data Engineer III will communicate with stakeholders and conduct research to develop a comprehensive understanding of relevant business needs and requirements.  In this role, the individual will identify and collect structured and unstructured data from various sources, evaluate the data to ensure that they meet analytic needs, and prepare the data for analysis.  The role will require advance business and technical requirements gathering and documentation (BRD, PRD), as well as data workflow design and presentations.  In addition, the Data Engineer III will select, apply, and assess advanced analytic models and techniques, and review and verify the results in preparation of reports and briefings to consult with stakeholders and communicate findings.  

Technical Design- Able to identify, analyze, specify, design, and translate functional design to technical design. Create and document technical designs for medium to high complexity solutions that may include integration with external systems.
  • Create and document technical designs for medium to high complexity solutions that may include integrations with external systems

·Facilitates peer technical design review

  • Design systems that span multiple technologies/platforms
  • Define and documents work processes/standards
  • Create and apply design standards across all applications
  • Design solutions to meet performance requirements and scalability expectations
  • Conduct data analysis and modeling to design medium to complex systems utilizing multiple technologies (may have a special area of expertise), including integration with external systems
  • Collect and curate data from disparate sources to perform data wrangling to clean, prepare, and standardize data
  • for consumption.
  • Design and create framework, program controls and services that can be utilized by other developers in creation of applications
  • Apply mathematical principles or statistical approaches to solve complex problems in scientific or applied fields
Data Modeling - Able to write, test, debug, and maintain data workflows for end-user adoption, productivity improvement and efficiency. 
  • Analyze data to discover and interpret patterns, trends, and variances
  • Assist with technical design
  • Troubleshoot and resolve technical issues
  • Develop knowledge of the company's applications
  • Facilitates peer code reviews
  • Research, analyze, and identify data requirements and business processes
  • Develop data science models to automate manual processes and to scale pipelines
  • Derive insight driven outcomes while utilizing the latest technologies and programming languages
  • Extract and transform data through normalization, field mapping, merging, and other techniques to standardize and prepare data for analysis
  • Collaborate with cross functional teams to identify and solve business intelligence and data issues
  • Proactively enhances systems for stability, efficiency, scalability and robustness
  • Develops, sponsors, and supports the introduction of new and improved methods, products, procedures, and technologies.  
  • Devise, makes recommendations, and guide implementation of corrective and/or preventive actions
  • Suggest better alternatives and flows to given requirements based on experience
  • Construct new data assets by combining data from multiple sources, which may be ambiguous, incomplete, or inconsistently formatted
  • Advanced knowledge of mathematical and statistical algorithms to apply toward decision analytic modeling
Requirements Elicitation – Ability to identify a desired future state that addresses a business problem.
  • Effectively uses interviewing skills to elicit, identify, and document business requirements
  • Precisely and consistently captures business problems
  • Prioritize requirements to identify the most critical needs
  • Uncover needs and value drivers that business partners and end users would not be able to articulate on their own
  • Articulate and incorporate extensive business knowledge into requirements
  • Obtain agreement and confirm understanding by clearly interpreting business requirements to business stakeholder
  • Drive consensus for a desired future state that meets the business problem and enterprise objectives
  • Influence stakeholders by clearly interpreting the future "to be" state
Requirements Management and Analysis – Ability to define, document, and manage business requirements to the smallest set that will provide the biggest impact in advancing business objectives.
  • Accurately translates business requirements into functionality
  • Manage requirements to meet business expectations
  • Document the current business process and the desired “to be” state to ensure efficient operation and integrity of data flow
  • Prioritize business requirements based on business needs
  • Understand business process complexity
  • Assess the risks of various solutions looking across multiple applications
  • Recommend changes to multiple business processes and communicate the changes and the “to be” state in business terms to business partners
  • Influence business partner requirements in support of enterprise objectives
  • Technical Design- Able to identify, analyze, specify, design, and translate functional design to technical design. Create and document technical designs for medium to high complexity solutions that may include integration with external systems.
    • Create and document technical designs for medium to high complexity solutions that may include integration with external systems

    Bachelor’s Degree in Computer Science, Data Science, Mathematics, or equivalent work experience in a related field required.

    5+ years’ of relevant experience in the design, execution, and the use of a wide array of data analysis techniques and tools in designing solutions required   
    5+ years’ experience in Query Languages such as SQL, SQLite or NOSQL required
    Must be self-motivated and able to work independently, with minimal supervision and as part of a team
    Detail oriented with excellent interpersonal communication skills (verbal and written), with the ability to interact with all levels of an organization
    Excellent customer service skills
    Excellent analytical skills: expertise in statistical and data science principles and methods with the ability to instruct others in these areas
    Advanced experience in data wrangling, blending, cleansing, and standardization required
    Advanced experience in data mining and machine learning analytics workflow and solution development required Experience implementing and working with on-premise and cloud infrastructure required
    Experience implementing and executing data migration, integration, and quality development in Hadoop and Spark clusters, and Scala preferred.
    Experience implementing and working with IaaS Cloud micro-services in Google, Amazon AWS, and Microsoft Azure preferred
    Practical experience in Neural Networks and other Machine Learning algorithms preferred
    Strong experience in developing data analytical modeling, risk based solutions, and recommended engines preferred Hands on experience with Data Mining and Machine Learning tools such as SAS, RapidMiner and Alteryx preferred Advanced experience with Java and/or Statistical program languages such as Python, R, SAS, etc. required
    Strong project management and organizational skills. 
    Experience using a version control system is a plus (GitHub, Subversion).
    Proven track record of delivering analytic solutions to solve complex problems using a data-driven approach and technical innovation.
    Demonstrated success in interpreting analytic output and providing strategic recommendations
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