Data Engineer

Overview Our client is hiring a Data Engineer to help power a platform that turns millions of public records and government documents into structured, interconnected data that delivers strategic insights for development, planning, and decision-making. The work involves ingesting diverse data sources such as permits, meeting records, environmental data, and regulatory filings, resolving references to the same entities across those sources, and organizing them into usable datasets that support risk evaluation, due diligence, policy tracking, and forward-looking analysis This is a hybrid position based in Boston, MA. Responsibilities Build and support data pipelines that ingest, transform, and organize diverse datasets Maintain existing workflows and contribute improvements focused on reliability and performance Help optimize schemas and queries used for analytics and downstream consumption Implement monitoring, validation, and quality checks across data workflows Assist with managing data storage systems such as warehouses and data lakes Investigate and resolve data-related issues in live environments Collaborate with engineers, analysts, and product partners to understand data needs Participate in code reviews and contribute to shared engineering practices Learn and adopt new tools and patterns as the data platform evolves Required Qualifications Bachelor’s degree in Computer Science, Engineering, or a related technical field 3+ years of experience in data engineering or a closely related role Strong SQL skills with experience working with relational datasets Experience building, maintaining, and supporting ETL or ELT pipelines Working knowledge of data modeling concepts and data quality practices Proficiency in Python and familiarity with at least one additional programming language Experience working in cloud environments such as AWS, Azure, or GCP Familiarity with data warehouses, data lakes, or analytical data stores Experience using workflow orchestration or scheduling tools Ability to troubleshoot data issues in production systems Clear communication skills and comfort collaborating across teams Nice to Have Experience supporting analytics, reporting, or operational data use cases Exposure to metadata-driven, semantic, or relationship-based data modeling Familiarity with highly connected or graph-like datasets Experience with streaming or incremental data processing Exposure to BI or reporting tools Experience preparing data for analytical or AI-driven workflows Interest in improving documentation, standards, or shared tooling What You Will Work On Build and support data pipelines that ingest, transform, and organize diverse datasets Maintain existing workflows and contribute improvements focused on reliability and performance Help optimize schemas and queries used for analytics and downstream consumption Implement monitoring, validation, and quality checks across data workflows Assist with managing data storage systems such as warehouses and data lakes Investigate and resolve data-related issues in live environments Collaborate with engineers, analysts, and product partners to understand data needs Participate in code reviews and contribute to shared engineering practices Learn and adopt new tools and patterns as the data platform evolves Technical Emphasis 40% Data Pipelines, Transformation, and Orchestration 30% SQL, Data Modeling, and Query Optimization 20% Cloud Data Platforms and Infrastructure 10% Python and Platform Support Day-to-Day Focus 75% Hands-on development and operational support 15% System improvements and optimization 10% Collaboration, planning, and documentation Compensation & Benefits Bonus eligible Benefits include Medical, dental, and vision coverage Paid time off 401(k) plan with company match (if applicable) Applicants must be authorized to work in the United States on a full-time basis now and in the future. #J-18808-Ljbffr