Lead/Senior Data Engineer

As the Lead Data Engineer, you will play a pivotal role in shaping the data infrastructure and product strategy. You will ideate alongside product, engineering, and clients to deploy innovative data products. Your responsibilities include: - Collaborating with product, engineering, and customers to develop impactful data products tailored to clients - Integrating intelligent features using AI and machine learning techniques - Architecting, developing, and optimizing end-to-end data pipelines on AWS - Leading the design and deployment of real-time data workflows and AI-enhanced products - Mentoring and nurturing a team of data engineers, promoting best practices - Overseeing the scaling of teams and infrastructure to support rapid growth - Developing systems using Python, SQL, PySpark, and Django - Utilizing databases and tools like Postgres, Redshift, Airflow, and MongoDB - Leveraging AI frameworks and libraries for advanced analytics Qualifications: - Minimum of 8 years of experience in data engineering or related roles - Proven track record in designing and deploying AWS cloud infrastructure solutions - Extensive hands-on experience with Postgres, Redshift, Airflow, MongoDB - Expertise in Python, SQL, PySpark, JavaScript - Strong background in software architecture and scalable development practices - Experience with front-end development using tools like Django, React - Tableau, Metabase, or similar visualization tools experience - Working knowledge of AI frameworks and libraries - Demonstrated experience in mentoring and scaling engineering teams - Excellent communication skills with effective client and end-user engagement - Ability to simplify complex technical concepts for non-technical stakeholders - Adaptability and agility to thrive in a fast-paced startup environment - Passion for fintech innovation and a strong desire to make a meaningful impact on the future of finance. As the Lead Data Engineer, you will play a pivotal role in shaping the data infrastructure and product strategy. You will ideate alongside product, engineering, and clients to deploy innovative data products. Your responsibilities include: - Collaborating with product, engineering, and customers to develop impactful data products tailored to clients - Integrating intelligent features using AI and machine learning techniques - Architecting, developing, and optimizing end-to-end data pipelines on AWS - Leading the design and deployment of real-time data workflows and AI-enhanced products - Mentoring and nurturing a team of data engineers, promoting best practices - Overseeing the scaling of teams and infrastructure to support rapid growth - Developing systems using Python, SQL, PySpark, and Django - Utilizing databases and tools like Postgres, Redshift, Airflow, and MongoDB - Leveraging AI frameworks and libraries for advanced analytics Qualifications: - Minimum of 8 years of experience in data engineering or related roles - Proven track record in designing and deploying AWS cloud infrastructure solutions - Extensive hands-on experience with Postgres, Redshift, Airflow, MongoDB - Expertise in Python, SQL, PySpark, JavaScript - Strong background in software architecture and scalable development practices - Experience with front-end development using tools like Django, React - Tableau, Metabase, or similar visualization tools experience - Working knowledge of AI frameworks and libraries - Demonstrated experience in mentoring and scaling engineering teams - Excellent communication skills with effective client and end-user engagement - Ability to simplify complex technical concepts for non-technical stakeholders - Adaptability and agility to thrive in a fast-paced startup environment - Passion for fintech innovation and a strong desire to make a meaningful impact on the future of finance.