Software Engineer 2 (Big Data)

Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper.
Data
Mid-Level Software Engineer
Hybrid
5,000+ Employees
2+ years of experience
Finance · Enterprise SaaS

Description For Software Engineer 2 (Big Data)

Come join the SBSEG Data Engineering team at IDC as a "Software Engineer - 2". We are leveraging big data technologies to gain new insights into our QuickBooks customer experience. Some of the technologies leveraged by our team include: Hadoop, Spark, and AWS Data Services. We foster an open team environment where we value direct interactions and working code above working in a cave.

Responsibilities: • Strong understanding of data engineering and dimensional design fundamentals, good at SQL, integration (ETL), front-end analysis / data visualization, learns new technologies quickly. • Good understanding of data warehouse schema design and granularity of the data. • Good understanding of data federation techniques and aggregation of data at scale from multiple source systems. • Designing and developing ETL pipelines across multiple platforms and tools including Spark, Hadoop and AWS Data Services. • Gathering functional requirements, developing technical specifications, and project & test planning. • Work with business users to develop and refine analytical requirements for quantitative data (view-through, clickstream, acquisition, product usage, transactions), qualitative data (survey, market research) and unstructured data (blog, social network). • Designing and developing schema definitions and support data warehouse/mart to enable integration of disparate data sources from within Intuit and outside, aggregate it and make it available for analysis. • Support large data volumes and accommodate flexible provisioning of new sources. • As a key member of the team drive adoption of new technologies, tools, and process improvements to build world class analytical capabilities for web analytics, optimization, experimentation and personalization. • Resolve defects/bugs during QA testing, pre-production, production, and post-release patches. • Work cross-functionally with various Intuit teams: Product Management, Project Management, Data Architects, Data Scientists, Data Analysts, Software Engineers, and other Data Engineers. • Contribute to the design and architecture of project across the data landscape. • Experience with Agile Development, SCRUM, or Extreme Programming methodologies. • Helps to align to overall strategies and reconcile competing priorities across organization.

Qualifications: • BS/MS in computer science or equivalent work experience. • Experience in developing data pipelines using Cloud service providers such as AWS, Azure, GCP etc • 2+ years of experience in developing data pipelines using Spark and Hive • Experience in developing complex data models/dimension models on datalake • Ideal candidate to have 3+ years of experience in end-to-end data warehouse implementations and at least 2 projects with 4TB+ data volume. • Good knowledge of Operating Systems (Unix or Linux). • Hands on experience in any of the programming languages (Shell scripting, Python, Java, etc). • Must have been through several full life cycle Data Warehousing implementations and involved in scalability and performance related design aspects in datalake and ETL. • Solid communication skills: Demonstrated ability to explain complex technical issues related to technical and non-technical audiences. • Demonstrated understanding of the Software design and architecture process. • Experience with unit testing and data quality automation checks • Should be results oriented, self-motivated, accountable and work under minimal supervision. • Excellent written, oral communication and presentation Skills.

Good to have: • Understanding of datamesh and microservices architecture • Knowledge of Big Data ecosystem like Hadoop M/R, Pig and Hive is a strong plus. • Conceptual understanding of Machine Learning is a plus. • Good understanding of any reporting tools such as Tableau, Pentaho or Jasper is a big plus. • Experience in design, development and deployment of one or more tools - ETL (Informatica, OWB, ODI), reporting (Business Objects, QlikView, Tableau) • Understanding of building highly resilient , fault tolerant data platforms to support 1000+ data applications • Programming languages like Java

Intuit offers a flexible work environment, allowing for hybrid work options that blend the best of in-person collaboration and the flexibility of virtual work.

Last updated a month ago

Responsibilities For Software Engineer 2 (Big Data)

  • Design and develop ETL pipelines across multiple platforms and tools
  • Gather functional requirements and develop technical specifications
  • Work with business users to develop analytical requirements
  • Design and develop schema definitions for data warehouse/mart
  • Support large data volumes and flexible provisioning of new sources
  • Drive adoption of new technologies and process improvements
  • Resolve defects/bugs during various stages of development and production
  • Work cross-functionally with various Intuit teams
  • Contribute to project design and architecture
  • Align strategies and reconcile competing priorities across organization

Requirements For Software Engineer 2 (Big Data)

Java
Python
  • BS/MS in computer science or equivalent work experience
  • Experience in developing data pipelines using Cloud service providers such as AWS, Azure, GCP etc
  • 2+ years of experience in developing data pipelines using Spark and Hive
  • Experience in developing complex data models/dimension models on datalake
  • 3+ years of experience in end-to-end data warehouse implementations
  • Good knowledge of Operating Systems (Unix or Linux)
  • Hands on experience in programming languages (Shell scripting, Python, Java, etc)
  • Experience with full life cycle Data Warehousing implementations
  • Solid communication skills
  • Understanding of Software design and architecture process
  • Experience with unit testing and data quality automation checks

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