Job Description

Junior Data EngineerThe Data Engineer designs, builds, and maintains reliable data pipelines, models, dashboards, and cloud data infrastructure that transform diverse source data into trusted, reusable data products for analytics, research, AI, and business decision-making. This role applies SQL, Python, modern data engineering practices, visualization tools, and AI-assisted development to improve data quality, automate workflows, and deliver scalable data and AI capabilities through internal tools, APIs, and lightweight applications. The position requires strong technical, analytical, communication, and project management skills, with experience in relational databases, cloud platforms, data visualization, and applied AI tools. The ideal candidate will be based in or near Philadelphia, PA, Chicago, IL, or Rockville, MD.Job ResponsibilitiesDesign, build, and maintain scalable, well-tested data pipelines and ELT/ETL workflows using SQL, Python, and cloud data platforms (e.g., BigQuery, Snowflake) to automate data ingestion, cleansing, and transformationModel and curate documented, reusable data products (transformations, semantic layers) that analytics, research, and AI systems can depend onCreate and maintain data visualization dashboards and reports for internal and external use (e.g., Power BI)Apply AI tools—including large language models (LLMs), AI-assisted coding, and machine learning techniques—to solve data problems, accelerate delivery, and improve data reliability, efficiency, and qualityPartner with research, product, data science, and design teams to incorporate the latest industry and business intelligence and to support their data infrastructure needsDocument best practices, data models, and current-state data documentationDeliver clear, actionable updates and insights to stakeholders, including Executive, Product, Data, and Design teamsDevelop, test, and maintain lightweight applications, internal tools, APIs, and user-facing interfaces on a modern tech stack (e.g., SpringBoot and React.js) to deliver data and AI capabilities to business usersDevelop, construct, test, and maintain cloud data architectures and infrastructure, applying DataOps and DevOps practices such as version control, CI/CD, and infrastructure as codeAdvanced working SQL knowledge and experience with relational databases, query authoring, and performance tuning, plus working familiarity with cloud data warehouses (e.g., BigQuery, Snowflake)Strong programming skills in Python (including Pandas) and demonstrated experience building data pipelines and automationHands-on experience applying AI to real problems—prompting and integrating LLMs, using AI-assisted development tools (e.g., GitHub Copilot, Claude, Cursor), and applying ML or statistical methods—with sound judgment about where AI does and does not add valueFamiliarity with modern data engineering tooling and practices, such as orchestration (Airflow, Dagster, or similar), transformation frameworks (e.g., dbt), and batch and streaming processingApplication development capability on a modern stack: building APIs and services (e.g., SpringBoot and React.js) to deliver data and AI features to end usersData visualization expertise with proven examples in Power BI or comparable toolsExperience performing root-cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvementStrong analytical skills working with large, unstructured datasetsAbility to build processes supporting data transformation, data structures, metadata, dependency, and workload managementStrong project management, communication, and organizational skills, with the ability to translate business needs into technical solutionsQualifications2+ years' experience building data pipelines and working with relational SQL databasesProficiency with Python (including Pandas) for data engineering and automationDemonstrated experience using AI tools to solve problems—e.g., integrating LLMs or LLM APIs, AI-assisted coding, or applying ML—in a professional or project settingFamiliarity with data visualization tools, particularly Power BI or equivalent (Tableau, Sigma, etc.)Minimum undergraduate degree in Computer Science, Engineering, or Math (equivalent practical experience considered)

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