Senior Data Solutions Specialist

ACT, API, Actuary, Advanced analytics, Alteryx, Amazon DynamoDB, Amazon Kinesis, Amazon Redshift, Amazon S3, Amazon Web Services, Analytics, Applied mathematics, Architecture, Attention to detail, Best practices, Business intelligence, Business requirements, Cloud, Communication skills, Computer, Computer science, Consulting, Continuous integration, Data QA, Data analysis, Data architecture, Data engineering, Data flow, Data governance, Data integration, Data integrity, Data management, Data modeling, Data processing, Data warehouse, Database, Decision-making, Design review, Docker, EDA, ELT, EMR, ETL, Education, Engineering, Enterprise architecture, Governance, IBM InfoSphere, IT, IT strategy, Implementation, Informatica, Informatica PowerCenter, Insurance, Integration, Kubernetes, MDM, Machine learning, Maestro, Metadata modeling, Microsoft SSIS, Multitasking, Office equipment, Operations research, Optimization, Organized, Performance tuning, Pricing, Problem solving, Product management, Productivity, Project management, QA, Roadmaps, SQL, Security, Self motivated, Software, Software deployment, Software development, Storage, Strategy, Streaming, Supervision, System integration testing, Systems design, Time management, Transformation, Unit testing, Usability, Virtualization, Web services
Full Time
Depends on Experience
Travel not required

Job Description

The purpose of this job is to understand the business landscape architecture, digest the business hurdles and build data solutions around it. This position will act as a data advisory member of the Actuarial, Business Intelligence (BI), Data & Analytics, Product & Pricing, and Data Program teams, as well as a collaborator and contributor to Enterprise Architecture. The position will collaborate with the functional areas to solve unique and complex Analytics, BI & Data Architecture, or business-significant problems, to build capabilities and help shape technology strategy. This position requires understanding of insurance domain, different Lines of Business (LOBs), and systems to collect data and come up with solutions to increase data maturity, effectiveness and to enable faster and better, data-informed decision-making.

ESSENTIAL DUTIES AND RESPONSIBILITIES

Builds advanced analytics solutions that ensure data integrity and information usability for enterprise-wide decision making. 

  • Builds data solutions that make the best use of the Cloud platforms like Amazon Web Service (AWS) and analytics services by understanding the business, technology, and data landscape.
  • Designs large scale, high-performance data processing systems (batch and/or streaming) to drive business growth and improve the product experience.
  • Collaborates with product management, BI and advanced analytics teams in implementing various data streams.
  • Leads data initiatives to ensure pipelines are reliable, efficient, testable, and maintainable.
  • Designs data models for optimal storage and retrieval and to meet critical product and business requirements.
  • Contributes to tooling and standards to improve the productivity and quality of output for data engineers across the company.
  • Assists in analysis of complex data elements and systems, data flow and in development of conceptual, logical, and physical data models as well as verification and implementation of ETL/ELT mappings and transformation logic.

Partners with project management and other engineering teams in determining overall data solutions.

  • Works collaboratively as a key contributor on a high performing team which delivers code and value.
  • Shares knowledge and contributes to solution application development on multiple large-scale, business critical systems.
  • Creates solution artifacts and presents to business and technology leaders.
  • Engages and partners with architecture teams to clearly understand the system design and roadmap.
  • Collaborates with the Enterprise Architecture team to conceptualize, design, and implement application and data architecture.

Leads and facilitates all technical and data aspects of several initiatives.

  • Analyzes and translates business needs into long-term solution data models.
  • Works with the development team to create conceptual, logical, and physical data models and data flows.
  • Contributes towards data governance and data quality best practices including design reviews, unit testing, code reviews, and continuous integration and deployment.
  • Collaborates with Enterprise Data Analytics (EDA) on direction for the data & analytics technologies, standards, processes, and architectures across the enterprise.
  • Reviews modifications of existing systems for cross-compatibility.
  • Collaborates in implementing components of data strategy – Master Data Management (MDM), data virtualization etc.
  • Updates and optimizes local and metadata models.
  • Evaluates implemented data systems for variances, discrepancies, and efficiency. 

SUPERVISORY RESPONSIBILITIES 

This role does not have supervisory responsibilities.

EDUCATION AND EXPERIENCE 

Bachelor’s degree in Computer Science, Applied Mathematics, Engineering, or any other technology related field required. Minimum 6 years of experience in a data integration (Cloud/Traditional) engineering related role required. Experience with data practices (security, data management and governance). Experience in operations research, machine learning or optimization a plus. Insurance experience a plus.

CERTIFICATES, LICENSES, REGISTRATIONS 

Cloud certification a plus preferably AWS.

KNOWLEDGE AND SKILLS

Experience with AWS data stack – S3, Glue, Redshift, Athena, EMR, Kinesis, DocumentDB, DynamoDB etc. Experience with establishing well-organized data lakes. Knowledge and experience with data movement tools –SSIS, Profisee/Maestro, Alteryx (these 3 preferred), PowerCenter Informatica, IBM Infosphere. Knowledge around enterprise web services and APIs connectivity, protocols and best practices for communication and integration between applications.  Strong familiarity with cloud-based services (AWS) and container technologies (Docker/Kubernetes) ·Experience setting up and optimizing data warehouses. Background in data modeling and performance tuning in relational and no-SQL databases. A self-starter mentality that thrives in a rapidly changing, fast-paced environment and tolerates ambiguity while demonstrating problem-solving with limited supervision. Strong analytical and time management skills. Self-motivated and able to handle tasks with minimal supervision. Must be organized, detail oriented, and able to multi-task. Ability to work well under pressure and deliver results with tight deadlines and under changing priorities, Ability to cross collaborate with multiple teams and offer value-added solutions to meet objectives. Strong verbal and written communication skills.  

PHYSICAL REQUIREMENTS  

Office environment – no specific or unusual physical or environmental demands and employees are regularly required to sit, walk, stand, talk, and hear.  

COMPETENCIES 

This position maps to the Individual Contributor level. Additional competencies required: None.

WORK ENVIRONMENT  

This position operates in an office environment and requires the frequent use of a computer, telephone, copier and other standard office equipment.

Dice Id : 10123200
Position Id : 6840086
Originally Posted : 2 months ago
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