Data Engineer, MCF

ARCADE team (Analytics team support MCF and BwP business) is seeking a highly motivated Data Engineer to solve innovative problems via business process and technology innovations. We are looking for an experienced Data Engineer to tackle complex and ambiguous problems that span numerous systems and organizations. As a Data Engineer, you will design, implement and support scalable data infrastructure solutions to integrate with multi heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, curate data that can be used in reporting, analysis and machine learning models. You will be exposed to cutting edge AWS big data technologies. You should have excellent business and communication skills to be able to work with business owners and Tech leaders to gather infrastructure requirements, design data infrastructure, build up data pipelines and datasets to meet business needs. You stay abreast of emerging technologies, investigating and implementing where appropriate.

Key job responsibilities
• Design, implement, and support data warehouse/ data lake infrastructure using AWS bigdata stack, Python, Redshift, QuickSight, Glue/lake formation, EMR/Spark, Athena etc.
• Develop and manage ETLs to source data from various Santos domain and SDO teams & operational systems and create unified data model for analytics and reporting.
• Creation and support of real-time data pipelines built on AWS technologies including EMR, Glue, Redshift/Spectrum and Athena.
• Collaborate with other Engineering teams, Product/Finance Managers/Analysts to implement advanced analytics algorithms that exploit our rich datasets for ML model development, statistical analysis, prediction, etc.
• Continual research of the latest big data and visualization technologies to provide new capabilities and increase efficiency.
• Build scalable and secure data infrastructure that will be used by BIEs to develop dashboards those are used by senior leadership.
• Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
• Working closely with team members to drive real-time model implementations for monitoring and alerting of risk systems.
• Manage numerous requests concurrently and strategically, prioritizing when necessary
• Partner/collaborate across teams/roles to deliver results.
• Mentor other engineers, influence positively team culture, and help grow the team

Basic 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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $91,200/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.