Manager, Data Engineering

Arlington, Virginia, USA

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Posted 3 weeks ago

Does the prospect of dealing with massive volumes of data excite you? Do you want to lead a team in 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 Engineering Manager to lead a team of Data Engineers. This role 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 Engineering Manager you will be working in one of the world's largest cloud-based data lakes. You should be an experienced manager capable of leading and inspiring a team of excellent data engineers. 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 extremely 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 lead 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 lead a team in building 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. Primary responsibilities will include managing a team of data and software engineers, interviewing, training and building a strong team, ongoing development of standard operating procedures and accountability for setting and meeting team goals. This high impact role will have an opportunity to lead a team to help 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.

Basic Qualifications

· 5+ years of experience as a Data Engineer or in a similar role
· Experience managing a data or BI team
· Experience with data modeling, data warehousing, and building ETL pipelines
· Experience leading and influencing the data strategy of your team or organization
· Experience in SQL
· A desire to work in a collaborative, intellectually curious environment.
· Have managed a team size of 8 or more members for a period of 2 or more years.
· Degree in Computer Science, Engineering, Mathematics, or a related field and 7+ years industry experience
· Experience managing a technical team
· Experience Communicating to senior management and customers verbally and in writing
· Must have two years of experience in the following skill(s):
· Developing and operating large-scale data structures for business intelligence analytics using: ETL/ELT processes; OLAP technologies; data modeling; SQL;
· Experience with at least one relational database technology such as Redshift, Oracle, MySQL or MS SQL
· Experience with at least one massively parallel processing data technology such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution

Preferred Qualifications

· Have managed a team size of 5 or more members for a period of 3 or more years.
· Industry experience as a Data Engineer or related specialty (e.g., Software Engineer, Business Intelligence Engineer, Data Scientist) with a track record of manipulating, processing, and extracting value from large datasets.
· Coding proficiency in at least one modern programming language (Python, Ruby, Java, etc)
· Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
· Experience building data products incrementally and integrating and managing datasets from multiple sources
· Experience leading large-scale data warehousing and analytics projects, including using AWS technologies – Redshift, S3, EC2, Data-pipeline and other big data technologies
· Experience hiring, developing, promoting engineers

Job tags: AWS Big Data Business Intelligence Data Warehousing Distributed Systems Engineering ETL Finance Hadoop Java MySQL Oracle Python Redshift Ruby Spark SQL