Boston, MA, 02133, USA
12 hours ago
Data Engineer (Remote)
Job Description A global law firm with nearly 1,400 lawyers and more than 3,000 employees across 19 offices in the United States, Europe, and Asia is looking to build out a data lake to encompass both internal and external data. The role is a long-term contract and remote. The firm is widely recognized for its expertise in corporate law, litigation, intellectual property, life sciences, technology, and venture capital, advising on transformative deals, IPOs, and complex regulatory matters. The firm has earned numerous workplace accolades, including being named to Fortune’s Best Companies to Work For and receiving honors such as Best Workplaces for Women, Best Workplaces for Flexibility, Best Workplaces for Giving Back, and Best Workplaces for Parents. The firm is looking to hire two Data Engineers to join their team building this greenfield data lake. Their primary responsibility will be to be hands-on development, focusing on data transformation and strategy initiatives using dbt-cloud (or dbt-core) for ETL workflows. They will collaborate with the Lead as well. Key Responsibilities Pipeline Development -Design, implement, and maintain ingestion pipelines for structured and semi-structured data. -Develop transformation workflows using dbt-cloud to ensure clean, modeled data for analytics. Data Product Delivery -Build domain-specific data products aligned with business requirements. -Ensure data quality, consistency, and adherence to governance standards. Collaboration -Execute tasks under guidance from the Lead Data Engineer. -Work with architects and other engineers to ensure interoperability across squads. Performance & Optimization -Monitor pipeline performance and optimize for scalability and cost efficiency. -Document processes and maintain version control for all data workflows. Compensation: $55/hr to $67/hr. Exact compensation may vary based on several factors, including location, skills, experience, and education. Employees in this role will enjoy a comprehensive benefits package starting on day one of employment, including options for medical, dental, and vision insurance. Eligibility to enroll in the 401(k) retirement plan begins after 90 days of employment. Additionally, employees in this role will have access to paid sick leave and other paid time off benefits as required under the applicable law of the worksite location. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements - 3+ years in Data Engineering in the cloud - experience in a Data Transformation and/or Data Engineering using dbt-cloud (or dbt-core) strongly preferred - Proficiency in Python, SQL, and Scala or Java for data processing - Familiarity with cloud platforms (Azure, AWS, or GCP) for data engineering - Knowledge of ingestion tools (e.g., Fivetran, Qlik) and modern data architectures (Lakehouse, Medallion zones - Big Data tool experience (Databricks preferred, Spark, Hadoop,, etc) - Law firm background - Familiarity with Unity Catalog, ingestion tools, and data governance principles - Knowledge of data modeling and integration with MDM systems
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