Top Entry Level Data & Analytics Jobs in Portland, ME

Build and maintain scalable data pipelines, infrastructure, data models, and APIs using Python, SQL, Airflow, Snowflake, dbt, Terraform, and cloud services. Ensure data quality, security, observability, and reliability while collaborating with analysts, product managers, and engineering teams. Own aspects of the FastAPI data service, including design, deployment, monitoring, and performance. Handle sensitive healthcare data in compliance with governance standards.

Leads a data engineering team and supervises one Data Engineer while designing, maintaining, and optimizing reliable data pipelines and infrastructure. The role integrates internal and external data sources, supports SaaS analytics dashboards and connected platforms, improves data-store performance, and ensures infrastructure quality, security, and uptime. Requires proficiency in Python, databases, distributed processing, orchestration, AWS, and machine learning.

Supports order-to-cash data integrity and physical fulfillment operations by improving processes, controls, data quality, automation, and reporting. The role collaborates with Business Systems, Finance, Supply Chain, and fulfillment teams on system implementations, audits, risk mitigation, KPI dashboards, and continuous improvement initiatives. It also documents best practices, monitors SLAs and KPIs, and advises leadership on process and technology improvements.

Conducts research and outreach to collect official local election documents, processes election and candidate data, and maintains Ballotpedia’s database. Monitors election schedules, audits and cleans data, interprets election materials, researches election laws, and improves workflows and local election coverage. The role requires careful, organized, neutral research, collaboration, concise communication, and effective use of online productivity tools in a fully remote environment.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Leads hands-on big data processing, data engineering, and analytics workflows using Azure Databricks, Python, and SQL. Develops insights and reporting with Power BI, Tableau, and Excel. Analyzes complex datasets, communicates findings to business stakeholders, manages competing priorities, meets deadlines, and promotes continuous improvement.

Analyzes and prepares customer data for successful migration to ServiceTitan. Works directly with customers to understand source databases, identify data issues, interpret database structures, and map data to ServiceTitan’s model. Writes queries to correct, reformat, and transfer data while coordinating with engineers, implementation teams, and onboarders. Manages shifting priorities, deadlines, project updates, and cross-functional communication to ensure accurate, timely data delivery.

Early-career Data Engineering Analyst supporting AIG’s Data Office through a rotational program. Responsibilities include developing cloud-based data pipelines, collecting and transforming data, building modern software systems, and supporting analytics and data science use cases. The role emphasizes data quality, security, compliance, collaboration, analytical problem-solving, and professional development through mentoring, masterclasses, and on-the-job experiences.

Analyze business performance, develop hypotheses, answer critical business questions, and build dashboards and reports in Sigma. Support budgeting, forecasting, data quality checks, and reconciliations while partnering with teams across growth, product, insurance, finance, and leadership. Serve as a trusted data advisor by answering metric and reporting questions and promoting data-driven decision-making.

Supports healthcare data analytics and research projects by evaluating diverse datasets, developing statistical models, validating and cross-referencing data, analyzing care and outcome patterns, and communicating findings to nontechnical stakeholders and clients. The role includes learning healthcare data types, SAS programming, research design methods, and quality improvement analytics while collaborating across multiple teams and managing concurrent projects.