OverviewCome join the Customer Success Data Engineering team in Mountain View as a Software Engineer - 2.We are leveraging big data technologies to gain new insights into our QuickBooks/Turbo Tax 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.What you'll bring
Bachelors/Masters in computer science or equivalent work experience.
experience in developing DB schemas, creating ETLs, and familiar with MPP/Hadoop systems.
Must have mastery of data warehousing technologies including data modeling, ETL and reporting. Ideal candidate to have 3+ years of experience in end-to-end data warehouse implementations and at least 2 projects with 4TB+ data volume.
Extensive experience with databases (Vertica, Netezza or oracle and AWS data services tech).
Good knowledge of Operating Systems (Unix or Linux).
Good understanding of Data ware House methodologies.
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 Database 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.
Knowledge of Big Data eco system 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)
How you will lead
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.
EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.