Top Entry Level Data & Analytics Jobs

Leads client-facing database migration and modernization engagements across AWS, relational, and NoSQL platforms. Designs migration architectures, data pipelines, ETL/ELT workflows, proof-of-concepts, and reusable technical accelerators. Facilitates executive conversations and workshops, translates complex technical solutions into business outcomes, and supports pre-sales opportunities. The role also develops GenAI-enabled migration tooling, influences senior stakeholders, and collaborates with distributed engineering, product, and data teams.

Conduct rapid political research by analyzing news, public records, campaign finance, voting histories, and legal documents; synthesize findings into concise research products for rapid response and communications teams; monitor national and local news; support department tasks as assigned.

Designs and maintains enterprise conceptual, logical, and physical ESG data models supporting sustainability, risk, finance, and treasury functions. Collaborates with data architects, technology teams, sustainability stakeholders, and enterprise architecture to align models with data governance, regulatory, and architectural standards. Defines data flows and sources, supports development projects, establishes ownership processes, and translates business requirements into scalable data solutions using SQL, UML, and data modeling tools.

Leads program-wide reporting strategy, governance, executive performance reporting, dashboard development, and reporting automation. Integrates cost, schedule, cash flow, earned value, risk, change, and forecast data into accurate, decision-ready reports. Coordinates with Program Controls, Finance, and leadership, ensures data quality and audit traceability, and supports federal, public-sector, and infrastructure reporting requirements.

Develops and maintains Power BI dashboards, reports, and analytics solutions for manufacturing operations. Analyzes operational data to identify trends and support factory decision-making, integrates machine-level data into fairlife’s Unified Factory Data Model, validates data quality, upholds governance and reporting standards, and trains end users on BI tools and data literacy.

Creates reports, data extracts, analyses, data processes, and business intelligence solutions. Builds and documents code for transforming, aggregating, and presenting data; learns organizational data sources and flows; communicates with colleagues; and participates in training. The role requires a technical bachelor's degree, strong mathematics and statistics skills, experience with SQL or programming/database languages, dashboarding tools, and Excel proficiency.

Manages wildfire debris-removal data, including field-data quality assurance, load-ticket reconciliation, invoice discrepancy identification, reporting, and project-document control. The role coordinates reconciled and voided tickets with contractors, prepares payment recommendations, exports client reports, maintains project records, and supports closeout activities. Work occurs in remote Alaska with extended shifts, weekends, and potentially 70–90 hours per week during the response period.

Analyze product, engineering, and machine data; build Python and SQL analyses; manage ETL pipelines across Amazon S3, Google Cloud Storage, and BigQuery; and develop Tableau or Streamlit dashboards. Translate stakeholder needs into KPIs, metrics, reliable datasets, and actionable insights while monitoring data quality, troubleshooting pipeline issues, and enabling self-service analytics.

Build AI-assisted interactive data visualizations, calculators, simulations, and internal web applications using Claude Code, React, and live data integrations. Translate ambiguous stakeholder needs into prototypes, then deploy and improve production-quality tools with reliable data pipelines, authentication, and performance. Collaborate with data engineering, establish reusable development patterns, train analysts on code-first workflows, and replace legacy BI dashboards with purpose-built applications.

Participates in a 12-month new-graduate development program while designing, building, deploying, and operating data architectures and pipelines. Develops processes for capturing, transforming, storing, and maintaining structured and unstructured data across distributed and local systems. Applies automation, big-data, artificial intelligence, and machine-learning techniques to support data integrity, compatibility, and evolving business requirements.