Top Entry Level Data & Analytics Jobs

Develop and maintain scalable data pipelines, ETL/ELT workflows, and data applications for reporting and analytics. Retrieve, parse, and process structured and unstructured data while designing and maintaining analytic solutions. Collaborate with analysts, developers, engineers, and data consumers in an agile environment. The role supports mission-driven client projects and requires eligibility for a Secret clearance.

Designs and develops SQL Server databases, including tables, views, procedures, functions, triggers, constraints, and secure code. Creates SSRS reports, SSIS packages, SSAS cubes, and data warehouses. Supports application development, database migrations, performance and concurrency issues, and backend requirements gathering.

Conduct quantitative and qualitative analyses of programs, grants, administrative operations, and financial data. Develop evaluation methods, reconcile and validate information, perform cost-benefit analyses, prepare reports, assess workflows and data systems, and recommend improvements to organizational processes and efficiency. Coordinate studies with stakeholders, communicate findings, and support management decision-making at the NIH.

Design, develop, test, and implement data engineering features using Python and PySpark. Build standalone scripts, perform complex data transformations, translate business requirements into technical solutions, troubleshoot data and software issues, and enhance existing frameworks. Apply object-oriented programming, coding best practices, automated testing, documentation, and large-scale data processing while collaborating with team members and working independently.

Designs and maintains scalable data infrastructure, including ETL/ELT pipelines, data lakes, warehouses, validation processes, and governance controls. Collaborates with architects and business stakeholders to translate requirements into reliable data solutions. Uses Docker, Kubernetes, cloud platforms, Spark, and orchestration tools to deploy and automate data services. Supports AI and automation initiatives involving LLMs and agents while improving data quality, security, and accessibility.

Transforms product-facing data into actionable insights through dashboard development, cyclical reporting, data validation, and analytics tools. The role uses Power BI, Excel, and SQL to create trusted reporting solutions, analyze trends and performance drivers, and support self-service analytics. It partners with Product, Technology, data engineering, and business stakeholders to translate requirements into scalable solutions and communicate recommendations effectively.

Lead the data engineering team and oversee the DBA team while driving GCP-based streaming and batch data platform initiatives. The role combines people leadership with hands-on work across BigQuery, dbt, Apache Flink or Dataflow, data quality, testing, observability, governance, and cost optimization. The manager will promote AI-assisted engineering practices, ensure transactional database reliability, and align data infrastructure with business and product objectives.

Maintains and delivers pricing reports, databases, queries, and business intelligence tools. Develops ad hoc reports and alerts, identifies reporting improvements, maintains data standards, collaborates with pricing and other departments, and supports the creation and distribution of analytics resources. Requires database and report-writing experience, advanced Excel, Access, SQL, and VBA skills, strong accuracy, documentation, communication, organization, problem-solving, and deadline management.

Research AI infrastructure and economics across GPU cloud providers, AI model developers, and AI tokenomics. Build company datasets, reconcile conflicting evidence, maintain financial and unit-economics models, analyze disclosures and technical materials, conduct interview research, draft research notes and charts, and support consulting projects with market and financial analysis.

Develops automated reporting, forecasting tools, SQL queries, Power BI dashboards, and analytical solutions. Partners with managers and departments to identify data-driven opportunities, analyze large datasets, define performance metrics, and improve decision-making. Tests and refines reporting tools for accuracy, usability, reliability, and long-term business value.