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Are you ready to unleash your full potential?We’re looking for people who are passionate about payments to chart Worldpay’s path to being the largest and most-loved payments company in the world.
About the team:
We are a part of WorldPay, who invented payment facilitation, enabling technology companies to provide integrated payment solutions, significantly expanding access to modern payment methods to SMBs, and rejuvenating end-user experience.
We are Payrix – a modern platform that provides Payfac as a service with a full suite of payments and risk management services built for vertical SaaS companies. With Payrix, SaaS providers can embed payments and financial services in their native experience and add a new revenue stream in a few weeks. We have a strong product-market fit and a clear moat that has resulted in an exponential growth of 100% YoY and the trend will continue.
What will you be doing
Technical Leadership
Provide expertise and guidance in big data technologies.
Extend and optimize our data lake: improve query performance and integrate more data sources.
Build ETL pipelines for our various data-driven services for our clients.
Build ETL pipelines and data materializations for internal data-driven reporting for historical analysis, risk assessment, projections, financial forecasting, etc.
Participate in the development and communication of data strategy and roadmaps across the technology organization to support product portfolio and business strategy.
Define high-level migration plans to address the gaps between the current and future state.
Lead the analysis of the technology environment to detect critical deficiencies and recommend improvement solutions.
Promote the reuse of data assets, including the management of the data catalog for reference.
Ensure that our data lake architecture and data catalog/dictionary are fully documented.
Help build user guides for writing efficient queries to utilize the data lake maximally.
Day-to-day governance for giving access to different parts of the data lake to different users after assessing their needs in coordination with infosec.
Ensure that all ETL code and configuration are properly maintained in the version control.
Drive digital innovation by leveraging innovative new technologies and approaches to renovate, extend, and transform the existing core data assets, including SQL-based, NoSQL-based, and Cloud-based data platforms.
Identify and improve parts of the platform to make it more robust and scalable.
Advise Payrix’s leadership on key technology and product roadmap considerations.
Align our technical decisions with Payrix’s broad strategic initiatives, while also advocating for needs specific to emerging new businesses.
Team Leadership
Dotted line responsibility for a distributed data engineering team (both full-time and contractors) while remaining hands-on.
Collaborate with and support the business intelligence team.
Collaborate with and support the data science team.
Mentor data engineers and software engineers in data principles, patterns, processes, and practices.
Project Management
Prioritize projects based on customer and internal needs in consultation with product management, engineering, operations, and finance departments.
Support teams as they deliver.
Support the needs of business intelligence, financial reporting, and data science teams.
Data Infrastructure
Build, implement and support data infrastructure extending the existing one.
Maintain different data materializations to speed up reporting needs.
Ensure reliable operations of various CDC and ETL pipelines.
Define, track, and guarantee Service Level Objectives.
Manage large and complex data sets that meet functional and non-functional business requirements.
Watch over Data Lake's operating expenses and strive to reduce them.
Design and oversee implementation of operational infrastructure related to the data pipelines
Desired Skills and Experience
Technical Skills
Programming Languages: Python, Java, Scala, C#, SQL
Storage: HDFS, AWS S3
Data Platforms: DataBricks, SnowFlake, RedShift
Data Lakes: Apache Hudi, Delta Lake
Relational Databases: Postgres, MySQL
NoSQL Databases: DynamoDB, MongoDB
Distributed Data Processing Engines: Apache Spark, Apache Flink, AWS EMR
Query Engines: Apache Presto, AWS Athena
Change Data Capture Solutions: Debezium, Qlik, Fivtran
Business Intelligence: QuickSight, Tableau, DBT, Power BI
Streaming: Kafka, RabbitMQ, ActiveMQ
Data Governance: AWS LakeFormation
Data Science and ML: NumPy, SciPy, Pandas, TensorFlow, PyTorch, SageMaker
Storage Formats: Arrow, Parquet, AVRO
Serverless Computing: AWS Lambda, Step Functions
Other AWS Services: IAM, RAM, EC2
Data Modeling & Architecture Patterns: Dimensional Modeling, Star Schema, Data Vault, Lake House Architecture
Soft Skills
Communication: Effectively communicate with both technical and non-technical stakeholders. Clear explanations and cross-department collaboration
Collaboration: Working closely with the mission-oriented product development teams where individual data engineers may be embedded.
Problem-solving: Having an eye for detail and the ability to solve complex problems efficiently.
Adaptability: Being adaptable to learn and integrate new tools and technologies as the tech landscape keeps evolving.
Critical Thinking: Analyzing situations, making informed decisions, and anticipating challenges.
Risk Management: Understanding risk factors related to data quality, security, and compliance.
Negotiation: Ability to advocate for data engineering needs and influence decision-making
Management Skills:
Leadership: Guiding and motivating the team, setting goals, and ensuring alignment with organizational objectives.
Project Management: Managing projects, timelines, and resources effectively.
Strategic Thinking: Aligning data engineering efforts with broader business strategies.
Cost Management: Managing data engineering infrastructure costs efficiently.
Change Leadership: Guiding teams through organizational changes and technological shifts.
What you bring
BS degree in engineering – computer science or related field
15+ years of successful and applicable hands-on experience in data engineering including end-to-end design and implementation.
5+ years of proven track record of managing or leading data engineering teams in designing and implementing efficient data models for large-scale datasets.
5+ years of hands-on experience with AWS cloud platform
Good understanding of network and data security architecture
Good experience in data lake architecture, governance, and implementation
Added bonus if you have:
Fintech or payments/banking product development experience
Experience in working in a start-up environment.
What we offer you:
A career at Payrix/WORLDPAY is more than just a job. It’s the change that shapes the future of fintech. At Payrix, we offer you:
A voice in the future of fintech
Always-on learning and development
Collaborative work environment
Opportunities to give back
Competitive salary and benefits
Privacy Statement
FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.
Sourcing Model
Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.
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