Key Responsibilities

• Data Architecture: Design andimplement scalable, efficient, and reliable data architectures, including datawarehousing, ETL/ELT, and data lake solutions.
• Data Pipelines: Develop andmaintain data pipelines using tools like mage.ai, Apache Beam, Apache Spark, orAWS Glue, ensuring data quality, integrity, and security.
• Data Engineering: Collaboratewith data scientists and analysts to develop and implement data models, datamining, and data visualization solutions.
• Data Quality: Implement dataquality checks, data validation, and data cleansing processes to ensurehigh-quality data.
• Scalability and Performance:Optimize data pipelines and architectures for scalability, performance, andreliability, ensuring low latency and high throughput.
• Collaboration: Work closelywith cross-functional teams, including Data Science, Product, and Engineering,to identify and prioritize data requirements and solutions.
• Mentorship: Mentor junior dataengineers and provide technical guidance and oversight.
• Staying Up to Date: Staycurrent with industry trends, emerging technologies, and best practices in dataengineering.
• Team Leadereship: Lead a small teamof 3-4 developers, providing guidance, mentorship, and code reviews
• Collaboration: collaborate withfront end and DevOps teams to ensure smooth deployment of code to AWS,architect, design and implement internal and external APIs

Requirements

• Education: Bachelor's orMaster's degree in Computer Science, Computer Engineering, or a related field.

• Experience: 6+ years ofexperience in data engineering, with a focus on building scalable dataarchitectures and pipelines.

Technical Skills:

• Programming languages: Python
• Data processing frameworks:Apache Airflow, Apache Beam, AWS Glue or similar tools.
•  Data storage solutions:relational databases such as MySQL, NoSQL databases such as MongoDB,cloud-based data warehouses such as Amazon Redshift.
• Data visualization tools:Tableau, Power BI, or D3.js, or similar tools.
• Cloud platforms: Amazon WebServices (AWS), Microsoft Azure, or Google Cloud Platform (GCP), with Amazonpreferred.
• Use of modern and popularPython libraries and Python ecosystem technologies and platforms.
• Use of one or more LargeLanguage Model and Natural Language Processing to aid in data acquisition, dataquality and data analytics.

Soft Skills:

•  Excellent communication andcollaboration skills.
• Strong problem-solving skills,with the ability to work independently.
• Experience with agiledevelopment methodologies.

Nice to Have:

• Certifications: AWS CertifiedData Engineer, Google Cloud Certified - Professional Data Engineer, or similar.
• Experience with: Machine Learning,OCR.
• Familiarity with:Containerization and Docker), orchestration and Kubernetes, serverlesscomputing.

What We Offer:

• Competitive salary and benefitspackage
• Opportunity to lead a smallteam and contribute to the growth and development of our core platform
• Collaborative and dynamic workenvironment
• Professional development andgrowth opportunities
• Flexible working hours andremote work options
• Access to cutting-edgetechnologies and tools
• Recognition and rewards foroutstanding performance