Overview
Come join Intuit as part of the Data Org Risk Data Analytics team as a Software Engineer 2 (data). We are looking for creative problem solvers with a passion for innovation to join our team and revolutionize the way the world does business. This is a full-time position in our Mountain View or Los Angeles, CA location. This position may also require some occasional travel to our other corporate offices (eg. Mountain View, Los Angeles, New York).The primary role of a Software Engineer 2 (data) is to provide timely technical, analytical and data support to the policy analyst and data science community to define, test, implement, and maintain strategies and procedures that will assist Intuit in growing revenue and profit by developing and maintaining innovative products and techniques in the target markets we serve.
What you'll bring
BS in Computer Science, Mathematics, or a similar field. Equivalent experience will be considered.
Object Oriented programming skills in Python, and a willingness to learn other languages (e.g. Bash, Scala, R) as needed.
Experience developing data processing applications using Spark.
Strong understanding of HADOOP-based technologies and systems, including Hive QL, MR, and Spark programming, Spark cluster/job optimization techniques, Lambda, streaming data with Kafka
Familiarity with database fundamentals including SQL, and schema design.
2+ years of experience integrating technical processes and business outcomes – specifically: data architecture and models, data and process analysis, data quality metrics / monitoring, developing policies / standards & supporting processes.
2+ years of hands-on data engineering experience.
1+ years DevOps experience including configuration, monitoring and version control.
Record of accomplishment working with data from multiple sources, willingness to dig-in and understand the data and to leverage creative thinking and problem solving.
Excellent interpersonal and communication skills, including business writing and presentations. Ability to communicate objectives, plans, status and results clearly, focusing on critical few key points.
Preferred Qualifications
MS in Computer Science, Mathematics, or a similar field.
1+ years of experience building and operating scalable and reliable data pipelines based on Big Data processing technologies like Hadoop, MR, Spark in the AWS cloud, Lambda, Kafka, S3.
Advanced programming skills in Python, Bash Shell. Familiarity with Scala and Microsoft .Net/C#.
2+ years of experience integrating technical processes and business outcomes – specifically: data architecture and models, data and process analysis, data quality metrics / monitoring, developing policies / standards & supporting processes.
2+ years of hands-on data engineering experience.
Familiarity with analytics, building and operating DW on Redshift, Big Query, or Snowflake MPP.
Demonstrated ability to work in a matrix environment, ability to influence at multiple levels, and build strong relationships.
Knowledge of enacting service level agreements and the appropriate escalation and communication plans to maintain them.
How you will lead
Work in the Risk Data Analytics data engineering team. The team has 10 engineers working on Risk & Compliance Management, Security, Fraud Prevention, EMR/Spark/Python data pipelines, Kafka streaming pipelines, Data Warehousing (DW), and Business Intelligence (BI) solutions.
Work closely with the Risk Decision Science team to design, build, deploy and operate their data science, data analytics solutions.
Work in fast-moving development team using agile methodologies.
Partner closely with Data Scientists, BI developers and Product Managers to design and implement data models, database schemas, data structures, and processing logic to support various data science, analytics, machine learning, and BI workflows.
Design and develop ETL (extract-transform-load) processes to validate and transform data, calculate metrics and model features, populate data models etc., using Spark, Python, SQL, Lambda, Kafka, and other approved technologies in the AWS cloud.
Lead by example, demonstrating best practices for code development and optimization, unit testing, CI/CD, performance testing, capacity planning, documentation, monitoring, alerting, and incident response in order to ensure data availability, data quality, usability and required performance.
Define SLAs for data availability and correctness. Automate data availability and quality monitoring and alerts. Respond to alerts when data delivery SLAs are not being met.
Communicate progress across organizations and levels from individual contributor to executive. Identify and clarify the critical few issues that need action and drive appropriate decisions and actions. Communicate results clearly and in actionable form.
New York $132,000 - $178,500
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.
