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Build large-scale batch and real-time data pipelines with data processing frameworks like Spark and AWS managed services.
Use best practices in continuous integration and delivery.
Help drive optimization, testing and tooling to improve data quality and our ability to use data to make product decisions.
Collaborate with other software engineers, ML engineers, Data Scientists, Data Analysts, and stakeholders, taking learning and leadership opportunities that will arise every single day.
Collaborate with the Analytics function to support their BI tools and initiatives to deliver the reliability, speed, and scalability of a data platform they’ll love working with.
Work in multi-functional agile teams to continuously experiment, iterate and deliver on new product and infrastructure objectives.
Optimize the existing data warehouse which will create a single version of the truth and standardize data into coherent formats for self-service
Keep abreast of new data storage, delivery, analysis, visualization, reporting techniques and software to develop more powerful data infrastructure.
Be a trusted technical advisor to customers and solve complex data challenges.
Inspire and lead others with your work ethic, business results, intrapersonal skills and willingness to see success based on team accomplishments vs. your individual achievements.
This role will report to the Data Engineering Manager
We're looking for a Senior Data Engineer with know how to work with high volume heterogeneous data, preferably with distributed systems on the AWS. - English is common on a daily basis, so the ability to conduct technical and complex conversations in English is a must.
Know how to work with high volume heterogeneous data, preferably with distributed systems on the AWS platform.
Know how to write distributed, high-volume services in Go, Java, Scala, or Python leveraging AWS managed services.
Knowledgeable about data modeling, data access, and data storage techniques.
Appreciate agile software processes, data-driven development, reliability, and responsible experimentation.
Want to own the software you write in production.
Understand the value of partnership within and across teams.
Care a lot about fostering a diverse culture that includes everyone and supports them being their authentic self. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our customers.
Experience building the infrastructure required for optimal ETL of data from a wide variety of data sources.
A successful history of manipulating, processing and extracting value from large disconnected datasets.
Superior understanding of database query languages and substantial knowledge in analytical approaches.
Bachelor’s degree in a technology-related field (data science, computer science, software engineering, etc.), with 5+ years’ data engineering experience.
Hands-on experience with data processing software and algorithms.
Experience in writing software in one or more languages: Java, Python, Go. Experience in SQL.
Experience managing client-facing projects, troubleshooting technical issues, working with cross-functional stakeholders.
Experience in working with/on data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures.
Excellent verbal and written communication skills.
Reflective, independent and eager learner (e.g., learns from mistakes, asks good questions, able to generate creative solutions to problems with minimal guidance)
High levels of integrity, autonomy, self-motivation and ability to work well in a team.