ABOUT THE JOB
Client-Facing Delivery
Lead the design, development, and implementation of scalable data pipelines and ETL/ELT processes for client engagements, delivering business intelligence and advanced analytics solutions with robust data quality controls
Collaborate directly with external clients to understand their data requirements and translate business needs into secure, compliant technical data engineering solutions
Ensure all client data solutions adhere to strict data governance frameworks and privacy protection standards
Internal Infrastructure & Data Management
Build internal data infrastructure from scratch or integrate with existing client systems, including secure data warehouses and data lakes that support organizational operations and analytics capabilities
Design and implement comprehensive data models for both client projects and internal systems, ensuring optimal performance, scalability, and data integrity
Develop and maintain data ingestion processes and APIs to seamlessly integrate data from multiple sources while maintaining data quality and security.
Data Governance & Security
Establish and enforce comprehensive data privacy protocols and data governance frameworks to ensure compliance with regulatory requirements and protect sensitive client data
Implement automated data quality monitoring systems to proactively identify and resolve data integrity issues across all data pipelines
Design and maintain data lineage tracking and audit trails to ensure full transparency and accountability in data processing workflows
Apply security best practices including data encryption, access controls, and secure data handling procedures throughout all data engineering processes.
Technology Integration & Innovation
Integrate AI/ML technologies (e.g., automated data processing, intelligent data validation, predictive data quality monitoring, and ML-powered analytics pipelines) into client deliverables and internal workflows
Leverage cloud-based platforms including Snowflake and Databricks to build scalable, cost-effective, and secure data solutions
Stay current with emerging data engineering technologies and data governance best practices to enhance both client outcomes and internal capabilities
WHAT WE'RE LOOKING FOR
Minimum Education/Experience
Bachelor's degree in Physics, Engineering, Computer Science, Information Systems, Mathematics, or a related technical field
At least 3 years of experience in data engineering, with proven experience building data pipelines for business intelligence and advanced analytics
Strong business acumen with experience working directly with external clients and internal cross-functional teams
Demonstrated track record of delivering complex data engineering projects that drive measurable business impact while maintaining data security and quality standards
Excellent communication skills, both verbal and written, with the ability to present technical concepts to non-technical stakeholders and clients
Experience with data privacy regulations and governance frameworks is essential
Experience in both client-facing and internal environments is a plus
Accounting, finance, or manufacturing domain knowledge is a plus
Technical and Other Skills
Core Technical Proficiency
Expert-level proficiency in SQL for complex data extraction, transformation, and modeling
Advanced programming skills in Python and SQL for data pipeline development and automation
Experience with data orchestration tools (e.g., Apache Airflow, dbt) and workflow management systems
Skilled in API development and integration, including RESTful APIs and data ingestion from various sources
Cloud & Data Platform Expertise
Extensive experience with cloud data platforms, specifically Snowflake and Databricks, for building enterprise-scale data solutions
Strong expertise in data modeling techniques and tools for designing efficient database schemas and data warehouse architectures
Deep understanding of ETL/ELT processes, data warehousing concepts, and modern data architecture patterns
Understanding of CRM/ERP systems (e.g., QuickBooks, Xero, NetSuite, SAP) and experience integrating them into data pipelines
Infrastructure & Development Operations
Familiarity with containerization technologies (Docker, Kubernetes) and cloud services (AWS, Azure, GCP)
Familiarity with version control systems (Git) and CI/CD practices for data engineering workflows
Experience with Agile/Scrum methodologies and project collaboration tools
Data Governance & Security
Understanding of data governance frameworks, data privacy regulations (GDPR, CCPA), and security best practices for handling sensitive financial data
Experience implementing data quality frameworks, data lineage tracking, and automated data validation processes
Knowledge of data encryption, access control mechanisms, and secure data handling procedures
PERKS & BENEFITS
Perks and benefits would include:
Remote setup
Company-provided equipment for seamless experience
Quarterly team activities to stay connected and engaged
