Data Engineer to build Data Pipelines in AWS

Amazon Web Services, Data architecture, Data engineering, Data warehouse, Data structure, Database architecture, Database design, ETL, Engineering, Architecture, Analytics, Data analysis, Data QA, Data flow, Data modeling, Database, Framework, Meta-data management, Software development, RDBMS, Python, SQL, Scripting, Statistics, Strategy, Transformation, Troubleshooting, UI, Normalization, NoSQL, Java, Integration testing, Documentation, Business intelligence, API, Big data, Computer science, OOP, Open source, Integration, Business process, Production, Product management, Process engineering, Organizational skills, Communication skills, Accessibility, Data Pipeline, AWS
Contract W2, Contract Independent, Contract Corp-To-Corp, 6 Months
Depends on Experience

Job Description

Note: This role is remote until COVID restrictions are in place after which team members are expected to be on-site in Princeton, NJ

Role Overview: We're looking for a strong Data Engineer who will be responsible for expanding and optimizing data and data pipeline architecture, as well as optimizing data flow and collection in AWS environment.

QUALIFICATIONS:

- 5+ years of experience in a Data Engineering role, Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
- Advanced working SQL knowledge and experience working with relational databases, query authoring and familiarity with a variety of databases
- Experience with database design principals including relationships and normalization, database structures, indexes and views and analyzing requirements and purpose of the database
- Experience building and optimizing big data data pipelines, architectures and data sets
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
- Strong analytic skills
- Experience building processes supporting data transformation, data structures, metadata, dependency and workload management
- Working knowledge of message queuing, stream processing, and highly scalable big data data stores
- Experience with relational SQL and NoSQL databases
- Strong skills with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Ability to architect end-to-end ETL pipelines

- Experience in building Data pipelines in AWS
- Experience with AWS Services

- Strong experience with AWS Lambda functions
- Experience with BI Tools
- Strong quantitative, analytical, process development, facilitation and organizational skills required
- Excellent documentation and verbal communication skills.
- Ability to communicate technical vision in clear terms to peers as well as outside of the engineering/development team

RESPONSIBILITIES:

- Responsible for expanding and optimizing data and data pipeline architecture, as well as optimizing data flow and collection
- Supports software developers, database architect, and data analysts on data initiatives and ensures optimal data delivery architecture is consistent throughout ongoing projects
- Must be self-directed and comfortable supporting the data needs of multiple teams, systems and products
- Responsible for optimizing or re-designing data architecture to support the next generation of products and data initiatives
- Develops and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity
- Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility
- Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes
- Writes unit/integration tests
- Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues
- Works closely with a team of frontend and backend engineers, product managers, and analysts
- Contributes to definition of company data assets (data models), and processes to populate data models
- Designs data integrations and data quality framework
- Designs and evaluates open source and vendor tools for data lineage
- Works closely with all business units and engineering teams to develop strategy for long term data platform architecture
- Contribute to development of a rapidly growing, integrated data warehouse that will provide a complete vision of the entire healthcare landscape

We look forward to reviewing your profile.

 

Thank you,

Talent Team @ SIALTP

Dice Id : 10432398
Position Id : 943DataEnginee
Originally Posted : 2 months ago
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