Lead, Data Engineering Frameworks and Quality Assurance

Position Summary

The Lead, Data Frameworks and Quality Assurance is responsible for designing and maintaining scalable data systems, establishing and owning common engineering frameworks, ensuring adherence to quality assurance standards, and driving operational excellence in data engineering processes. This role requires strong technical expertise and a commitment to delivering high-quality, reusable frameworks and infrastructure that align with organizational goals.

Primary Responsibilities

· Own the design, development, and maintenance of common engineering frameworks for data pipelines, orchestration, quality assurance, error handling, and logging.

· Oversee the integration and implementation of DevOps practices and tools for data engineering workflows, ensuring seamless deployment and operational efficiency.

· Develop and enforce frameworks, standards, and best practices for data quality assurance, testing, validation, and monitoring.

· Collaborate with QA Automation Engineers to develop and maintain robust testing tools, including test cases, frameworks, and automated processes for validating data pipelines and infrastructure.

· Lead the Data Engineering Center of Excellence (COE), fostering innovation, knowledge sharing, and collaboration across teams.

· Oversee the implementation of automated testing and monitoring systems to ensure data integrity, consistency, and reliability.

· Create and maintain technical documentation, training materials, and onboarding resources for engineering frameworks to ensure broad team adoption and effective usage.

· Optimize data pipelines and infrastructure for performance, scalability, and cost-efficiency.

· Monitor and troubleshoot issues in data systems, proactively addressing inefficiencies and incidents.

· Ensure adherence to data governance and compliance standards such as GDPR and CCPA, integrating best practices for data security and privacy into frameworks and workflows.

· Mentor and guide team members, fostering a culture of quality, accountability, and continuous improvement

Required Skills

· Deep understanding of modern data infrastructure, data pipeline frameworks, and data quality assurance practices.

· Expertise in error handling and logging frameworks for robust and reliable data engineering processes.

· Experience designing and maintaining reusable frameworks for common data engineering workflows (e.g., ETL/ELT, schema validation, and logging).

· Strong knowledge of DevOps practices, including CI/CD pipelines, infrastructure as code, and monitoring tools.

· Familiarity with data validation and testing tools like Great Expectations or Soda.

· Experience with data warehousing platforms like Snowflake, Databricks, or Redshift.

· Proficiency in programming languages such as Python, Java, or Scala, with a strong emphasis on modular and reusable code development.

Qualifications

· Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.

· 5+ years of experience in data engineering, infrastructure design, or quality assurance roles, with at least 2 years in a leadership capacity.

· Demonstrated experience in designing, implementing, and maintaining reusable engineering frameworks for team-wide adoption.

· Proven track record of collaborating with QA Automation Engineers to deliver high-quality testing solutions.

About Focus Financial Partners

Focus is a leading partnership of fiduciary wealth management and related financial services firms. Focus provides access to best practices, greater resources, and continuity planning for its affiliated advisory firms, which serve individuals, families, employers, and institutions with comprehensive financial services. Focus firms and their clients benefit from the solutions, synergies, scale, economics, and best practices offered by Focus to achieve their business objectives. For more information about Focus, please visit www.focusfinancialpartners.com.

The annualized base pay range for this role is expected to be between $120,000 - $140,000. Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed and the applicant's skill set. The base pay is just one component of the total compensation package for employees. Other reward may include an annual cash bonus and a comprehensive benefits package.