Data Engineer, Finance Technology
1 month ago
FinTech is seeking a talented Data Engineer to join our innovative team of software engineers and data experts who are shaping the future of our finance data platform. We are committed to build a robust data lake with clear semantics, effective governance, and a streamlined ML data pipeline that enables predictive modeling, optimizes financial resource allocation, enhances claims processing, and insurance management capabilities for Amazon's rapidly growing and dynamic businesses. Our powerful data platform drives data-driven decision-making for finance and risk management by providing timely, accurate, and actionable insights.
As a Data Engineer, you should be an expert with technical components (e.g. Data Modeling, ETL and Reporting), infrastructure (e.g. hardware and software) and their integration. You should have deep expertise and passion in working with large data sets, data visualization, building complex data processes, performance tuning, bringing data from disparate data stores and programmatically identifying patterns. 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. The candidate is expected to be able to build efficient, flexible, extensible, and scalable ETL and reporting solutions. You should be enthusiastic about learning new technologies and be able to implement solutions using them to provide new functionality to the users or to scale the existing platform. Excellent written and verbal communication skills are required as the person will work very closely with diverse teams. Having strong analytical skills is a plus. Above all, you should be passionate about working with huge data sets and someone who loves to bring data-sets together to answer business questions and drive change.
Ideal candidates thrive in this fast-paced environment and relish working with large volumes, enjoy the challenge of highly complex business contexts, and, is a passionate about data and analytics. In this role you will be part of a team of engineers and supporting Amazon's expanding global footprint.
Key job responsibilities
* Design, implement, and support data lake infrastructure using AWS big data stack, Python, Redshift, Quicksight, Glue/lake formation, EMR/Spark/Scala, Athena etc. providing secured access to large datasets.
*Interface with customers or business stakeholders, gathering requirements and delivering complete data solutions.
* Model data and metadata to support ad-hoc and pre-built reporting.
* Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
* Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
* Tune application and query performance using profiling tools and SQL.
* Analyze and solve problems at their root, stepping back to understand the broader context.
* Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use.
* Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for datasets.
* Triage possible courses of action in a high-ambiguity environment, and adopt quantitative analysis and business judgment when making design decisions.
* Mentor other engineers, influence positively team culture, and help grow the team.
A day in the life
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
We are open to hiring candidates to work out of one of the following locations:
Jersey City, NJ, USA | Seattle, WA, USA
BASIC QUALIFICATIONS
- 3+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Knowledge of batch and streaming data architectures like Kafka, Kinesis, Flink, Storm, Beam
- Bachelor's degree
- Proficiency in at least one modern programming language such as Java, Scala, or Python.
PREFERRED QUALIFICATIONS
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Master's degree
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