Job Description

Senior Data Engineer

Location US-CA-Mountain View ID 2020-14707 Category Data

Overview

Intuit’s Small Business Group (SBG) develops and brings to market the products that small businesses and accounts depend on every day for their success. These products include accounting products (QuickBooks), payments, payroll and others.

The SBG Data Engineering team is looking for a Senior Data Engineer with a winning track record in Big Data, Data Warehousing, Visualization and Data Web Services. We’re using data in groundbreaking ways to uncover customer insights, personalize customer experiences, and provide a unified customer view across all SBG products.

Responsibilities

• Work in the Small Business Group (SBG) Data Engineering team. The team works on Data Platform, Data Services, Real-time Analytics, Data Warehousing, Business Intelligence and more.
• Work closely with the internal customers to design, build, deploy and operate their data warehouse capabilities.
• Ensure consistent use of common dimensions and adhering to existing design patterns to integrate the customer data with existing ecosystem data in the data mart.
• Work with Product Managers and Data Scientists to identify datasets needed for deep customer insights and for building operational propensity models.
• Work with ingestion developers to bring required source datasets into the data warehouse.
• Design a data model appropriate for customer business use cases.
• Design and develop ETL code to populate the data model.
• Define SLAs for data availability and correctness.
• Lead by example, demonstrating best practices for unit testing, CI/CD, performance testing, capacity planning, documentation, monitoring, alerting, and incident response.
• Respond to alerts when SLAs are not being met.
• Work with BI developers to ensure that the data warehouse is providing the required data and the required performance.
• Serve as technical “go to” person for our core technologies – AWS, Redshift, EMR, Spark, Hadoop, Vertica, Qlikview, Tableau, Cassandra and others.
• Demonstrate strong implementation aptitude to translate objectives into a scalable solution to meet the needs of the end customer while meeting deadlines.
• Demonstrate commitment to your professional development by attending conferences, taking classes, giving technical presentations, and participating in developer communities inside and outside of Intuit.

Qualifications

• BS in Computer Science. MS preferred.
• Excellent interpersonal and communication skills, including business writing and presentations. Ability to clearly communicate objectives, plans, status and results, focusing on a few critical key points.
• 5+ years of hands-on software engineering experience.
• 5+ years of experience integrating technical processes and business outcomes – specifically: data and process analysis, data quality metrics/monitoring, data architecture, developing policies/standards & supporting processes.
• 5+ years of experience building data warehouse solutions using MPP technology.
• 3+ years of experience developing solutions using Big Data technologies like Hadoop, Hive, EMR, Spark.
• Mastery of Dimensional Modeling.
• Mastery of Advanced SQL.
• Strong object-oriented programming experience in Java, Python, Ruby or similar.
• Experience with various offerings from AWS, including S3, EMR, Redshift, Data Pipeline, Athena and Kinesis.
• Experience working with business leadership to design data solutions that meet business needs.
• Experience leading successful cross-functional agile development teams. This includes gathering requirements, designing solutions, creating JIRA stories, managing the backlog, planning sprints, leading daily standups, giving product demos, and reporting status to senior management.
• Experience operating a mission critical data warehouse. This includes monitoring ETL, data availability, and data quality, and coordinating a response (using PagerDuty) when SLAs are not being met.
• Experience working with large, complex source systems, and working with developers of those systems to dig in and understand the complexities of the data.

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