Job
Description
As a Lead Data Engineer at Relcu, Inc., you will have a significant impact on shaping the data infrastructure and product strategy of the company. Your role will involve collaborating with product, engineering, and clients to develop innovative data products that cater to the specific needs of our customers. You will be responsible for designing, building, and maintaining scalable data pipelines and workflows on AWS while also guiding and mentoring a team of engineers. Your expertise in AI and machine learning will be crucial in enhancing the intelligence of our solutions. Key Responsibilities: - Product Ideation & Innovation: - Brainstorm with product, engineering, and clients to create impactful data products. - Utilize AI and machine learning techniques to incorporate intelligent features into our offerings. - Technical Leadership & Architecture: - Architect and optimize end-to-end data pipelines on AWS. - Lead the design of real-time data workflows and AI-enhanced products. - Ensure cost and performance optimization across all data solutions. - Team Mentorship & Growth: - Mentor and guide a growing team of data engineers, instilling best practices in software architecture. - Cultivate a culture of collaboration, continuous learning, and innovation within the team. - Infrastructure & Workflow Optimization: - Scale teams and infrastructure to support rapid growth and changing business requirements. - Implement cost management and performance optimization strategies effectively. - Technical Development & Collaboration: - Develop systems using Python, SQL, PySpark, and Django for front-end development. - Utilize decision science, AI, and ML to deploy impactful data products. - Translate technical concepts into clear insights for clients and end-users. - Tool & Technology Expertise: - Work with databases and tools like Postgres, Redshift, Airflow, and MongoDB to support the data ecosystem. - Incorporate AI frameworks and libraries for advanced analytics in solutions. Qualifications: - Experience: - Minimum of 8 years in data engineering, software development, or related roles. - Proven track record in designing and deploying AWS cloud infrastructure solutions. - Hands-on experience with Postgres, Redshift, Airflow, MongoDB, and real-time data workflows. - Demonstrated experience in integrating AI and machine learning into data products. - Technical Skills: - Proficiency in Python, SQL, PySpark, JavaScript. - Strong background in software architecture and scalable development. - Experience in front-end development with tools like Django, React. - Knowledge of visualization tools such as Tableau, Metabase. - Experience in creating and deploying data products using decision science, AI, and machine learning. - Leadership & Communication: - Experience in mentoring and scaling engineering teams. - Strong communication skills for effective client and end-user engagement. - Ability to simplify complex technical concepts for non-technical stakeholders. - Startup & Fintech Mindset: - Ability to thrive in a fast-paced, early-stage startup environment. - Passion for fintech innovation and a desire to make a meaningful impact on the future of finance. As a Lead Data Engineer at Relcu, Inc., you will have a significant impact on shaping the data infrastructure and product strategy of the company. Your role will involve collaborating with product, engineering, and clients to develop innovative data products that cater to the specific needs of our customers. You will be responsible for designing, building, and maintaining scalable data pipelines and workflows on AWS while also guiding and mentoring a team of engineers. Your expertise in AI and machine learning will be crucial in enhancing the intelligence of our solutions. Key Responsibilities: - Product Ideation & Innovation: - Brainstorm with product, engineering, and clients to create impactful data products. - Utilize AI and machine learning techniques to incorporate intelligent features into our offerings. - Technical Leadership & Architecture: - Architect and optimize end-to-end data pipelines on AWS. - Lead the design of real-time data workflows and AI-enhanced products. - Ensure cost and performance optimization across all data solutions. - Team Mentorship & Growth: - Mentor and guide a growing team of data engineers, instilling best practices in software architecture. - Cultivate a culture of collaboration, continuous learning, and innovation within the team. - Infrastructure & Workflow Optimization: - Scale teams and infrastructure to support rapid growth and changing business requirements. - Implement cost management and performance optimization strategies effectively. - Technical Development & Collaboration: - Develop systems using Python, SQL, PySpark, and Django for front-end development. - Utilize decision science, AI, and ML to deploy impactful data products. - Tr
