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Data Engineer
Job Description
As a Data Engineer at Personetics, you will be a key player in designing, implementing, and optimizing data solutions leveraging Airbyte for data integration, DBT for advanced modeling, and Apache Airflow for workflow orchestration. This role requires a physical presence on-site for 50% of the time, contributing to the success of our AI-driven financial solutions while ensuring the seamless flow and utilization of data.
Responsibilities
1. Airbyte Integration:
Design and implement data pipelines using Airbyte connectors to facilitate efficient and reliable data extraction, ingestion, and integration.
Collaborate with cross-functional teams to ensure seamless data flow across our financial data landscape.
2. DBT Modeling and Transformation:
Utilize DBT to create modular and scalable datasets, enabling advanced analytics and reporting tailored to the financial domain.
Work closely with data analysts and scientists to align DBT models with specific business requirements.
3. Apache Airflow Workflow Orchestration:
Design, implement, and optimize workflows using Apache Airflow to automate and schedule critical data tasks.
Ensure the performance and efficiency of Airflow workflows, focusing on the security and compliance requirements of the financial sector.
4. Data Integration and Collaboration:
Collaborate with cross-functional teams to seamlessly integrate data solutions into Personetics' AI-driven financial applications.
Facilitate smooth data flow between different components of the data infrastructure.
5. Database Management:
Design and implement databases based on data modeling principles, prioritizing optimization for performance, reliability, and security.
Collaborate with database administrators to ensure the integrity and security of financial data storage.
6. Data Quality Assurance:
Implement data quality checks and validation processes within DBT and other tools to maintain high-quality data standards.
Proactively identify and address data quality issues, ensuring compliance with financial regulations.
7. Documentation and Training:
Document implementation processes, configurations, and best practices.
Provide training and support to end-users, analysts, and team members.
8. Innovation and Continuous Improvement:
Stay abreast of industry trends, emerging technologies, and financial regulations.
Propose and implement improvements to data engineering processes to enhance our AI-driven financial solutions.
Qualification
Nice to have:
About The Financial Services.
Serves over 120 banks and financial institutions across 30 global markets. See how your bank can harness the power of AI to engage customers and increase revenue with financial data-driven personalized customer engagement, PFM, and money management platform.
Data Engineer
Salary
60,000-100,000/month
Position Level
Job Level
Experienced Hire
Job Type
Hiring Until
05/25/2024
