DescriptionTeam Falcon is seeking a Data Engineer to help implement leading flagship multi-year projects to inject automated planning and reporting, predictive forecasting, and help shape an end UI, built on the AWS Data Lake. We support flexible working options blending working at home and in office from either Sydney, Brisbane or Melbourne Key job responsibilities
Deliver on data architecture projects and implementation of next generation financial solutions.
Manage AWS resources including EC2, RDS, Redshift, Kinesis, EMR, Lambda etc.
Build and deliver high quality data architecture and pipelines to support customer reporting needs.
Interface with other technology teams to extract, transform, and load data from a wide variety of data sources.
Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
Collaborate with business users, development teams, and operation engineering teams to tackle business requirements and deliver against high operational standards of system availability and reliability
Dive deep to resolve problems at their root, looking for failure patterns and suggesting fixes
Build and enhance software to extend system, application, or tool functionality to improve business processes and meet end user needs while working within the overall system architecture
Diagnose and resolve operational issues, perform detailed root cause analysis, respond to suggestions for enhancements
Identify process improvement opportunities to drive innovation
About the teamWW Operations Finance is poised for a revolution. Historically, automation and technical infusion has taken a back-seat to important financial functions such as controllership, financial oversight, risk mitigation, and strong investment analysis. Finance is set to be the Chief Story Tellers, and along the way inject machine learning, BI, advanced analytics and technical tools – built to suit finance and business needs.We are open to hiring candidates to work out of one of the following locations:Dallas, TX, USA | San Jose, CA, USA | Seattle, WA, USABasic Qualifications
1+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
Experience with one or more scripting language (e.g., Python, KornShell)
Preferred Qualifications
Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $81,000/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
