Join a growing and successful fintech company! This Jobot Job is hosted by: Jonathan Santo Are you a fit? Easy Apply now by clicking the “Apply” button and sending us your resume. Salary: $120,000 – $150,000 per year A bit about us: We are a team of companies that prides ourselves on being champions for compliance in the finance space. We are dedicated to supporting compliance professionals by integrating technology, consulting, and education to help clients manage the constantly evolving regulatory environment. Our network of firms serves over 7,000 clients, including many of the world’s leading financial institutions. Clients across our network benefit from a full range of premier governance, risk, and compliance (GRC) services, including consulting, technology solutions, managed services, analytics, and outsourcing. Why join us?
FULLY REMOTE Competitive compensation Comprehensive benefits package Long term growth and stability Job Details Job Details: We are on the hunt for an experienced, dynamic, and passionate Data Engineering Manager to join our technology-driven team. This permanent, remote position offers the opportunity to work with a team of talented professionals in the technology industry. We are a fast-growing fintech company, and we need a data expert who can manage, guide, and grow our data team. In this role, you will be responsible for managing the data engineering team, developing data pipeline architectures, and implementing systems for tracking data quality and consistency. Responsibilities: Lead, mentor, and manage a team of data engineers, fostering a collaborative and innovative environment. Design, develop, and maintain scalable data processing systems, ensuring data accuracy and security. Implement and manage data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it. Work closely with all business units and engineering teams to develop strategy for long term data platform architecture. Develop and implement data standards, ensuring data quality across the organization. Build and maintain data pipelines, architectures and data sets using tools such as RabbitMQ, Elasticsearch, Scrapy, Beautiful Soup, and more. Work with AWS, Azure, GCP, Kubernetes, Redis, Jenkins, Postgres, ETL, NoSQL, SQL, and other technologies. Collaborate with data scientists and architects on several projects. Qualifications: Bachelor’s degree in Computer Science, IT, or a related field. 10+ years of experience in data engineering, data science, or a related field. 3+ years of proven experience managing a team of data engineers or a similar team. Experience with web scraping and utilizing frameworks such as Scrapy, Beautiful Soup. Selenium or similar frameworks Strong experience with data architectures, data modeling, and data management. Understanding of Elasticsearch indices, complex queries and search optimization. Experience in the fintech industry is preferred but not required. Familiarity with AWS, Azure, GCP, Kubernetes, Redis, Jenkins, Postgres, ETL, NoSQL, SQL. Strong understanding of data pipeline and workflow management tools. Excellent problem-solving and analytical skills. Strong leadership and project management skills. Excellent communication and interpersonal skills. Ability to work in a fast-paced, dynamic environment. Must be self-motivated and able to work independently, with a proven ability to manage multiple tasks and projects simultaneously. Interested in hearing more? Easy Apply now by clicking the “Apply” button.
PostgreSQL Establishing interpersonal relationships Analytical skills data-management Amazon Web Services (AWS) Data Engineering Azure Fast-paced environment indices Elasticsearch Communication data-modeling Google Cloud Platform (GCP) Search Engine Optimization (SEO) Redis Project management Data Science Self-motivation Problem-solving Data Architect web-scraping SQL Kubernetes ETL Leadership NoSQL Jenkins