Senior Data Engineer

WHO WE ARE

Apex Fintech Solutions (AFS) powers innovation and the future of digital wealth management by processing millions of transactions daily, to simplify, automate, and facilitate access to financial markets for all. Our robust suite of fintech solutions enables us to support clients such as Stash, Betterment, SoFi, and Webull, and more than 20 million of our clients' customers.

Collectively, AFS creates an environment in which companies with the biggest ideas in fintech are empowered to change the world. As a global organization, we have offices in Austin, Dallas, Chicago, New York, Portland, Belfast, and Manila.

If you are seeking a fast-paced and entrepreneurial environment where you'll have the opportunity to make an immediate impact, and you have the guts to change everything, this is the place for you.

AFS has received a number of prestigious industry awards, including:

• 2021, 2020, 2019, and 2018 Best Wealth Management Company - presented by Fintech Breakthrough Awards
• 2021 Most Innovative Companies - presented by Fast Company
• 2021 Best API & Best Trading Technology - presented by Global Fintech Awards

Apex Fintech Solutions is seeking a Senior Data Engineer to join our data engineering team, responsible for designing, developing, and maintaining robust data solutions that empower decision-making and enhance business processes. You will leverage your expertise in Python, MS SQL, Big Query SQL, and cloud platforms (GCP, AWS, or Azure) to optimize data pipelines, enhance data models, and contribute to analytical insights.

Proficiency in Airflow will be critical to orchestrate workflows efficiently. While this is not a direct management position, you will play a leadership role by guiding junior data engineers, promoting best practices, and fostering technical excellence in the team. You will also collaborate with cross-functional teams to deliver scalable and reliable solutions aligned with business objectives.

• Data Engineering and Pipeline Development: Design and implement scalable data pipelines to extract, transform, and load structured and unstructured data across multiple platforms. Utilize Airflow to orchestrate complex workflows and ensure efficient task execution. Optimize data workflows using Python, MS SQL, and Big Query SQL for performance and reliability.
• Cloud Technologies and Infrastructure: Build and optimize data solutions leveraging cloud platforms, including GCP, AWS, or Azure. Drive adoption of cloud-based tools and techniques for scalability, reliability, and cost-effectiveness.
• Data Modeling and Database Management: Develop and maintain data models and schemas that align with business needs and support analytics initiatives. Troubleshoot and resolve database performance issues, collaborating with DBAs when necessary.
• Data Quality and Analysis: Conduct detailed analysis of datasets to validate accuracy, completeness, and logical consistency. Design automated data validation and quality checks to ensure consistent data integrity.
• Leadership and Mentorship: Provide mentorship and technical guidance to junior data engineers, ensuring their development aligns with team goals and standards. Promote best practices in coding, data engineering, and technical documentation through active collaboration and code reviews.
• AI Tools and Data Innovation: Leverage AI-powered tools to enhance productivity, automate data engineering workflows, and drive innovation within the team. Stay informed about emerging trends in AI and data technologies to implement cutting-edge solutions.
• Cross-Functional Collaboration: Collaborate with product managers, analysts, and other technical teams to identify data requirements and craft impactful solutions. Partner with software engineers to integrate and scale data pipelines across broader product architectures.
• Problem Solving and System Reliability: Investigate and resolve data and pipeline-related issues in production environments, minimizing downtime and ensuring system reliability. Implement recovery and monitoring procedures for pipelines, leveraging cloud-based tools.
• Continuous Learning and Process Improvement: S…