Does the prospect of dealing with massive volumes of data excite you? Do you want to be a part of building data engineering solutions that process billions of records a day in a scalable fashion using AWS technologies? Do you want to create the next-generation tools for intuitive data access? Amazon’s Finance Tech team needs a Data Engineer to play a role that will be part of the Knowledge Services group within FinTech whose vision is to become an authoritative source of all finance data, build services to process big data at scale, and empower customers with actionable insights using advanced analytics. This is an opportunity to work on building one of the largest finance data platforms in the world. Think of millions of customers, billions of transactions and petabytes of data.
As a Data Engineer you will be working in one of the world’s largest cloud-based data lakes. You should be skilled at helping engineers navigate priorities and communicating clear expectations with customers. You should be knowledgeable in the architecture of data warehouse solutions for the Enterprise using multiple platforms (EMR, RDBMS, Columnar, Cloud). You should have experience in the design, creation, management, and business use of large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. You should be able to architect highly efficient data and reporting structures, making a tradeoff between scalability, performance and user functionality needs, using expert knowledge in software development technologies. You should develop long term domain/technology strategies and significantly influence the process and engineering standards in the team. You should be able to perform design reviews and offer feedback on design, integration, performance and scalability issues. Serve as an authority in the area of technical and domain expertise and mentor, develop, and train the engineers. Above all you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive change.
In this role you will build a large-scale near real time data ingestion, calculation engine, and reporting solutions for Finance teams across the globe for Amazon. This person will work across other Amazon engineering teams and business teams in planning, designing, executing and implementing this analytical platform. This high impact role will have an opportunity to design and build our data infrastructure and work with emerging technologies such as Redshift and associated AWS cloud services while driving business intelligence solutions end-to-end: business requirements, workflow instrumentation, data modeling and ETL. You should be an expert at designing, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data lake and into end-user facing applications. The role requires someone who loves data, understands enterprise information systems, has a strong business sense, and can lead a team to put these skills into action.
An ideal candidate for this role will have prior experience managing multiple customer-facing teams, lot of experience in heterogeneous technologies in DW space (map/reduce, columnar DBs etc.,) and will be capable of technical deep-dives yet verbally and cognitively agile enough to participate in strategy discussions with Amazon’s senior management team. You will be accountable for driving the entire product life-cycle, from platform product definition through specification, coding, quality assurance and launch to the world.
· 3+ years of experience as a Data Engineer or in a similar role
· Experience with data modeling, data warehousing, and building ETL pipelines
· Experience in SQL
· Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
· Extensive experience working with AWS with a strong understanding of Redshift, EMR, Athena, Aurora, DynamoDB, Kinesis, Lambda, S3, EC2, etc.
· Experience with coding languages like Python/Java/Scala
· Experience in maintaining data warehouse systems and working on large scale data transformation using EMR, Hadoop, Hive, or other Big Data technologies
· Experience mentoring and managing other Data Engineers, ensuring data engineering best practices are being followed
· Experience with hardware provisioning, forecasting hardware usage, and managing to a budget.
· Exposure to large databases, BI applications, data quality and performance tuning
· Experience partnering with business owners directly to understand their requirements and provide data which can help them observe patterns and spot anomalies.
· Experience with web technology to develop dashboards.
· Practical Knowledge of Linux or Unix shell scripting
· Experience in processing large volume of data.
· Strong troubleshooting and problem solving skills
· Demonstrated experience in dealing with Senior Management on addressing their reporting and metrics requirement
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