Data Engineer designing robust data pipelines and cloud infrastructure for OnTheList’s sustainable flash sales. Collaborating on analytics and ensuring data quality for business insights.
About the role
- Data Engineer responsible for backend data engineering tasks, developing ETL processes for legal data integration. Collaborating with teams to ensure efficient data pipelines and governance.
Responsibilities
- Design, construct, and maintain data pipelines (ETL processes) to integrate large volumes of legal data efficiently and securely from various sources
- Develop data lake and data warehouse solutions, implementing best practices for data ingestion, storage, and retrieval
- Establish and deploy comprehensive data governance and security frameworks including data access controls, compliance measures, and data classification
- Collaborate with cross-functional teams, including analysts, attorneys, and IT professionals, to understand data requirements and design backend solutions that meet their needs
- Assess and prioritize data initiatives based on business objectives, best practices, and partner/practice need to ensure alignment with strategic goals
- Design and implement testing strategies for data pipelines, validating data integrity, accuracy, and performance throughout the workflow
- Create and maintain thorough documentation for data architectures, pipelines, and transformations, and processes to ensure transparency and knowledge sharing
- Build and optimize automated data workflows to streamline ingestion, transformation, and processing, reducing manual effort and improving efficiency
- Optimize data storage and retrieval processes to improve performance and scalability, leveraging cloud-based technology such as Azure
- Participate in and contribute to data quality enhancement planning and implementation for new projects
- Stay current with the latest industry trends and best practices in data engineering and analytics, continuously evaluating and implementing new tools and techniques to enhance our data infrastructure
- Provide technical support and troubleshooting assistance for data-related issues, working proactively to identify and resolve potential problems
- Collaborate with cybersecurity and compliance teams to ensure data security and regulatory compliance
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a technology-related field
- 7+ years of related work experience, preferably in a legal or regulatory environment
- Proven experience leading data engineering projects, including requirements gathering, architecture design, development, testing, and deployment
- Experience with Microsoft Fabric or a combination of Azure Synapse Analytics, ADLS Gen 2, Synapse SQL Pools, Azure Data Factory (ADF) and/or other Azure data platforms
- Experience with the Microsoft Power Platform, such as Power BI, Power Automate, Power Apps, or other similar tools
- Strong SQL Experience including complex queries, stored procedures, SSIS, SSRS
- Experience building data pipelines using Python/PySpark
- Proven experience designing and implementing data architectures, including system requirements, technology selection, and governance
- Expertise in end-to-end multi-layered data architectures (e.g., bronze/silver/gold), managing data from raw ingestion to business-ready datasets while ensuring quality, lineage, and documentation
- Strong data modeling skills, including conceptual, logical, and physical models for optimized storage and retrieval
- Proven ability to test data pipelines for accuracy, consistency, and performance, including unit and integration testing
- Experience in migrating data from on-premises databases and servers to Azure Cloud environments is preferred
- Experience with version control; knowledge and experience with GitHub is a plus
- Ability to present technical ideas in business-friendly and user-friendly language.
Benefits
- Health insurance
- 401(k) matching
- Flexible work arrangements
- Professional development opportunities
Job title
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Not specified
Degree requirement
Tech skills
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