Sr Data Engineer

Responsibilities:
- Architect all phases of software engineering including requirements analysis, application design, code development and testing with a focus on business intelligence dataset development
- Design reusable components, frameworks, and libraries
- Contribute and make recommendations to the design and architecture to enable secure, scalable, and maintainable solutions
- Clearly articulate the implications of design/architectural decisions, issues and plans to technology leadership
- Work collaboratively with People Analytics on the development and production of standard datasets to drive actionable decision making and reporting stability
- Conduct design and code reviews to ensure code developed meets business needs, coding best practices guidelines, unit testing, security, and scalability and maintainability guidelines
- Work very closely with architecture groups and drive solutions
- Assist with updating infrastructure components
- Use engineering best practices following an Agile methodology to deliver high-quality emerging tech solutions
- Communicate with impact - influence and negotiate effectively with all internal and external stakeholders to achieve win-win solutions that advance organizational goals
- Grow and maintain knowledge of and leverage emerging technologies
- Develop and analyze highly complex system standards, thresholds, and recommendations to maximize system performance
- Analyze project requirements and develop detailed specifications for new data warehouse reporting requirements
- Research API calls and make necessary changes to meet the business, contractual, security, performance needs
- Assesses and interprets customer requests for feasibility, priority, and complexity
- Create and maintain internal process documentation
- Support projects and change initiatives aligned to key priorities of People Analytics and People Analytics customers
- Understands priorities and organizes prescribed and non-prescribed work to meet or exceed deadlines and expectations
- Proactively keeps data secure and decommissions legacy content in our environment
- Serve as a resource to others within the People Analytics community; mentors other data engineers; provides explanations and information to others on difficult issues, problems, and solutions
- Works with minimal guidance; seeks guidance on only the most complex tasks
- Coaches, provides feedback, and guides others within the People Analytics community
 
Ideal Background:
- Ideal candidate would have experience in the Human Capital space, working with the backend data warehousing of human capital systems
 
Requirements:
- 3+ years of data engineering experience
- 3+ years of full lifecycle application, software development experience
- 3+ years of modern programming language such as Python, Java, and Scala
- 2+ years of SDLC experience in an Agile environment
- Working knowledge of the following business and technology concepts: APIs, CI/CD, Big Data, data architecture and governance
- Experience with Cloud technologies and platforms such as Docker, OSE, Kubernetes, AWS, Snowflake, and Azure
- Experience with Jenkins, GitHub, Big Data technologies like Spark
- Experience using IDEs such as Eclipse, JBoss, IntelliJ
- Relational database experience
- Experience ingesting and working with large and complex datasets
- Experience gathering requirements from end users
 
Preferred Skills:
- Experience in data extraction, manipulation, and management
- Experience researching issues, investigating data accuracy, and performing quality checks
- Project Management skills
- Ability to work independently and collaborate effectively with others
- Experience creating user stories using the “As a (role), I want (function) so that (business value)” methodology
- Basic understanding of statistical methodologies and measurements
- Experience leading people (directly or indirectly) or large-scale projects
- 1+ years in an agile environment or with agile tools such as Rally or Swift
 
Interview process:
- Video phone or in person?
o Video
- How many rounds?
o 1-3
- How technical will the interviews be?
o Technical questions will be asked in the relevant technologies to the role in which the interviewee has experience
 

Required Skills : Requirements: - 3+ years of data engineering experience - 3+ years of full lifecycle application, software development experience - 3+ years of modern programming language such as Python, Java, and Scala - 2+ years of SDLC experience in an Agile environment - Working knowledge of the following business and technology concepts: APIs, CI/CD, Big Data, data architecture and governance - Experience with Cloud technologies and platforms such as Docker, OSE, Kubernetes, AWS, Snowflake, and Azure - Experience with Jenkins, GitHub, Big Data technologies like Spark - Experience using IDEs such as Eclipse, JBoss, IntelliJ - Relational database experience - Experience ingesting and working with large and complex datasets - Experience gathering requirements from end users

Basic Qualification :

Additional Skills :

Background Check : Yes

Drug Screen : Yes