Data Engineer-6336

Responsibilities

• Build and modify high-complexity ETL and data pipelines to efficiently extract, transform, and process data from large-scale datasets.
• Develop and maintain monitoring and alerting systems that proactively identify data, infrastructure, and workflow issues.
• Design data warehousing solutions and optimize queries and pipelines for large-scale data processing.
• Collaborate with attorneys, data scientists, engineers, and other technical and non-technical stakeholders to understand data requirements, sources, dependencies, and timelines.
• Lead end-to-end data engineering initiatives across cross-functional teams, including planning, documentation, stakeholder coordination, system design, and execution.
• Identify potential data and system issues early and implement solutions that improve reliability, efficiency, and operational visibility.
• Communicate technical concepts and project status clearly and concisely to both technical and non-technical audiences.

Internal Responsibilities

• Attend regular internal practice community meetings.
• Collaborate with your itD practice team on industry thought leadership.
• Complete client case studies and learning material, including blogs and media material.
• Build material to contribute to the Digital Transformation practice.
• Attend internal itD networking events, both in person and virtually.
• Work with leadership on career fast-track opportunities.

Required Qualifications And Skills

• 5–7+ years of experience in data engineering or a closely related field.
• Expert-level SQL experience, including experience with relational or distributed query engines such as Presto, PostgreSQL, or MySQL.
• Expert-level Python programming experience.
• Expert-level experience building and managing ETL/data pipelines using pipeline orchestration tools such as Airflow or comparable technologies.
• Demonstrated experience leading data engineering efforts on large, cross-functional projects involving both technical and non-technical stakeholders.
• Demonstrated ability to design and deliver high-complexity monitoring and alerting systems.
• Strong written and verbal communication skills, with the ability to communicate concisely and effectively.
• Experience working independently while collaborating effectively across multiple stakeholder groups.
• Strong understanding of data privacy and security considerations in data engineering environments.

Preferred Qualifications And Skills

• Experience using AI to accelerate project delivery or building AI-enabled components to automate workflows for non-technical stakeholders.
• Experience supporting highly regulated industries, such as legal, compliance, finance, security, or privacy.
• Experience mentoring junior data engineers or other technical team members.
• Experience working in startups, small organizations, or ambiguous environments with broad ownership and scope.
• Experience with data loss remediation or related data protection initiatives.
• Volunteer or internship experience with a law firm or experience working in privacy-related environments.
• Startup, entrepreneurial, or self-employed experience demonstrating broad ownership and initiative.

Benefits

We provide comprehensive medical benefits, a 401k plan, paid holidays, and more.