Senior Data Engineer

Gibson Dunn is a leading global law firm advising clients on significant transactions and disputes. Our exceptional teams craft and deploy creative legal strategies that are meticulously tailored to every matter however complex or high-stakes. The firms work is distinguished by a unique combination of precision and vision.

Based in the US the Senior Data Engineer will be responsible for designing building and operating the data platforms that power enterprise reporting analytics and artificial intelligence across the firm. The role spans the full data lifecycle: ingesting data from diverse operational systems curating it within scalable data lakes and warehouses and delivering high-quality model-ready datasets to analysts data scientists and AI/ML workflows. This role blends hands-on data platform engineering with database and reporting expertise.

This role reports to the Director Product & Engineering.

Primary applications and platforms include:

• Document Management: iManage (cloud) SPM Litera CAM
• Finance: Aderant Expert Sierra Chrome River Time Entry
• HR: PeopleSoft Workday
• Enterprise data lake data warehouse and analytics platforms

Responsibilities include:

Data Platform Data Lake & Pipeline Engineering

• Design build and maintain scalable data lakes warehouses and lakehouse environments (on-premises and/or cloud) to consolidate data from diverse enterprise sources.
• Develop and orchestrate reliable automated ETL/ELT pipelines to ingest transform and deliver structured and unstructured data.
• Implement layered data architectures (e.g. raw / curated / consumption or bronze / silver / gold layers) that support reuse across reporting analytics and AI workloads.
• Monitor and maintain pipelines proactively to ensure high availability timeliness and data freshness.
• Apply data quality validation and error-handling practices to ensure accuracy completeness and consistency.
• Establish and maintain data lineage cataloging and metadata to support governance and traceability.

Data for AI / Machine Learning

• Collaborate with data scientists and ML practitioners to curate prepare and serve high-quality datasets for model training fine-tuning and inference.
• Build and maintain pipelines that transform raw enterprise data into clean model-ready datasets.
• Support feature engineering feature stores and reusable data products for AI/ML use cases.
• Enable AI-oriented data patterns such as embedding pipelines and retrieval-augmented workflows and support integration with vector stores where appropriate.
• Partner with engineering teams to operationalize data workflows that keep models supplied with reliable well-governed data.

Database Administration & Operational Support

• Administer monitor and maintain relational database environments (on-premises and/or cloud).
• Perform and automate routine operations including:
  • Backups and restores (full differential and log).
  • Integrity checks and consistency validation.
  • Index maintenance and statistics updates.
• Monitor and troubleshoot performance issues including CPU memory and I/O bottlenecks as well as blocking deadlocks and long-running queries.
• Implement performance tuning strategies such as query optimization execution plan analysis and index design and review.
• Manage database availability and resilience including high availability clustering and disaster recovery planning and validation.
• Coordinate patching upgrades and service releases.
• Ensure security and compliance through access controls permissions encryption auditing and vulnerability mitigation.
• Support scheduled jobs ETL processes and automated data workflows.

Query & Data Performance Optimization

• Write efficient queries and transformations for reporting and analytical workloads.
• Reduce dataset size and improve refresh and processing performance.
• Understand and optimize the impact of joins filters and aggregations across large datasets.

Analytics & Reporting

• Translate business questions into queries metrics and visualizations.
• Develop maintain and optimize dashboards and reports using leading BI tools (e.g. Tableau Power BI or comparable platforms).
• Design semantic models and data sources for reporting including fact/dimension modeling (star and snowflake schemas) data shaping and transformation.
• Optimize report performance through query tuning and data model optimization (aggregations and relationships).

Collaboration & Leadership

• Participate actively in group and cross-functional meetings.
• Deliver clear coherent report-outs to senior management.
• Work with interdepartmental groups to innovate and improve the firms data capabilities.
• Mentor and train data engineers on the data platform and its business applications.

Qualifications:

• Strong analytical and problem-solving skills with a track record of owning systems end-to-end.
• Ability to work independently and manage competing priorities in operational environments.
• Effective communication with both technical and business teams.
• Proven ability to collaborate across departments to identify and drive improvements.

Experience:

• 10 years of experience building and supporting enterprise data platforms pipelines and application databases.
• Bachelors degree in Computer Science Information Technology Engineering or a related field (or equivalent experience).
• Experience managing business-critical data systems in a global environment.
• Proficiency with SQL and at least one programming/scripting language commonly used in data engineering (e.g. Python).
• Hands-on experience with data warehousing data lakes or lakehouse architectures.
• Experience building ETL/ELT pipelines and working with data orchestration tools.
• Experience with cloud data platforms (e.g. AWS Azure Google Cloud Snowflake Databricks or comparable).
• Experience preparing and serving data for AI/ML model training fine-tuning or inference.
• Familiarity with distributed data processing frameworks (e.g. Apache Spark).
• Familiarity with pipeline orchestration tools (e.g. Apache Airflow or similar).
• Familiarity with ML and AI concepts including feature stores vector databases and embedding/RAG pipelines.
• Familiarity with automation and scripting (e.g. Python PowerShell or Bash).
• Exposure to DevOps MLOps or CI/CD practices for data or BI deployments.

Gibson Dunn will consider for employment qualified Applicants with Criminal Histories in a manner consistent with the requirements of local law.

Compensation & Benefits:

The annual compensation range for this position is$150000 - $200000. The salary offered within this range will depend upon qualifications and other operational considerations.

Benefits offered for this position include health care; retirement benefits; paid days off including sick time and vacation time; parental leave; basic life insurance; Flexible Spending Accounts; as well as discretionary performance-based bonuses.

For technical difficulties with our online application please contact us at. Our recruiting support team will respond as soon as possible.

Gibson Dunn is committed to ensuring equal employment opportunities for all qualified applicants including individuals with disabilities. We strive to ensure an inclusive and accessible hiring experience. The Firm will provide reasonable accommodations to qualified individuals with disabilities to enable participation in the application and recruitment process unless doing so would impose an undue hardship in accordance with applicable laws and regulations.

If you require a reasonable accommodation to complete an application participate in an interview or otherwise take part in the recruitment process please contact us at . Please note this is a dedicated email inbox established exclusively to assist applicants with accommodation request related to the recruitment process. Inquiries about the status of an application or other non-accommodation matter will not receive a response.