Staff Engineer - Data Engineering

About the role

This position is a key role in the development, test, and deployment of complex solutions. Key responsibilities include building data strategy, driving technical and data architecture, leading efforts, representing engineering in cross-functional teams, and supporting risk management.

Responsibilities

• Build data strategy for broad or complex requirements with insightful and forward-looking approaches that go beyond the direct team and solve large open-ended problems.
• Participate in the strategic development of methods, techniques, and evaluation criteria for projects and programs.
• Drive all aspects of technical and data architecture, design, prototyping and implementation in support of both product needs as well as overall technology data strategy.
• Provide leadership and technical expertise in support of building a technical plan and backlog of stories, and then follow through on execution of design and build process through to production delivery.
• Guide a broad functional area and lead efforts through the functional team members along with the team’s overall planning.
• Represent engineering in cross-functional team sessions and able to present sound and thoughtful arguments to persuade others.
• Adapt to the situation and can draw from a range of strategies to influence people in a way that results in agreement or behavior change.
• Collaborate and partner with product managers, designers, and other engineering groups to conceptualize and build new features and create product descriptions.
• Actively own features or systems and define their long-term health, while also improving the health of surrounding systems.
• Absorb and resolve production issues as they arise.
• Develop and implement tests for ensuring the quality, performance, and scalability of our application.
• Actively seek out ways to improve engineering and data standards, tooling, and processes.
• Supporting the company’s commitment to risk management and protecting the integrity and confidentiality of systems and data.

Requirements

• Education and/or experience typically obtained through a Bachelor’s degree in computer science or related technical field.
• Eight or more years of relevant related experience.
• Six or more years of experience in the development of complex data platform, distributed systems, SaaS, cloud solutions, micro services.
• Six or more years of experience in the development of Data Warehouse, Big Data – structured & unstructured platforms, real-time & batch processing, data standards.
• Four or more years of experience in development of Business Intelligent Solutions.
• Two or more years of experience in development / operationalization of Artificial Intelligence / Machine Learning Models / Model development life cycle activities (implementing feature engineering, data pipelines, model operationalization, model monitoring).

Qualifications

• Demonstrated experience in delivering business-critical systems to the market.
• Ability to influence and work in a collaborative team environment.
• Extensive experience implementing Data Warehouse (Star / Snow flake schemas) using SQL Server or equivalent, Big Data – HDFS, Elastic Search, ETL process development using IBM Infosphere or equivalent, Reusable Frameworks.
• Experience with implementing data science solutions using Python, Spark, PySpark, R, Data Robot.
• Experience with event-driven architecture and messaging frameworks (Pub/Sub, Kafka, RabbitMQ, etc).
• Working experience with cloud infrastructure (Google Cloud Platform, AWS, Azure, etc).
• Knowledge of mature engineering practices (CI/CD, testing, secure coding, etc).
• Knowledge of Software Development Lifecycle (SDLC) best practices, software development methodologies (Agile, Scrum, LEAN etc) and DevOps practices.
• Attention to detail.

Skills

• Knowledge of AI/ML Model Frameworks like Tensorflow, Sage Maker, Scikit, PyCharm.
• Big Data Platforms (Cloudera, S3).
• Database platforms (Oracle, SQL Server) with experience around performance aspects and replication.
• Computer language experience (Python, PySpark, and R).
• Knowledge of Aerospike, Scality S3, Elastic Search.
• Monitoring and Alerting systems experience (AppDynamics) or other observability measures.
• Knowledge of ACH/EFT.
• Experience in development / operationalization of Artificial Intelligence / Machine Learning Models / Model development life cycle activities (implementing feature engineering, data pipelines, model operationalization, model monitoring).
• FinTech experience.
• Kubernetes experience.

Benefits

The company offers healthcare coverage, a 100% Company Safe Harbor Match on your first 6% deferral immediately upon eligibility, a 401(k) Retirement Plan, flexible time off, 12 weeks of Paid Parental Leave, Maven Family Planning, and much more!