Top Entry Level Data Engineer Jobs

Entry-level Junior Data Engineer to help build and maintain cloud data pipelines into BigQuery using tools like Fivetran and Python. Contribute to Medallion (bronze/silver/gold) layers, data transformations (dbt), basic data quality checks, CI/CD practices, documentation, and governance while learning cloud engineering, orchestration, and observability under senior engineers.

Support building and maintaining ETL/ELT data pipelines and cloud data workflows. Work with senior engineers and cross-functional teams to implement, test, deploy, and document data processes. Continuously learn cloud technologies, SQL, and Python/PySpark, follow coding best practices, and contribute to process improvements in an Agile environment.

Develop and design data pipelines, optimize data delivery and automate processes to support end-to-end solutions in various settings.

The role involves structuring and ingesting customer data, setting up ETL pipelines, and providing solutions for data export and import.

Build and maintain data marts, materialized views, and ETL/ELT pipelines in an AWS-hosted data lake. Design and optimize data workflows, monitor infrastructure health and data quality, support PostgreSQL migrations, collaborate with cross-functional teams, and ensure compliance with federal data security (FISMA/NIST 800-53).

The Data Engineer will build and scale Baseten's internal data platform, designing data models and pipelines while enabling self-service analytics and ensuring data reliability.

This role offers training for aspiring Data Engineers, focusing on technology of choice, interview preparation, and skill enhancement with guidance on OPT STEM extension.

Entry-level rotational Data Engineer role focused on SQL Server development, SSIS package creation, data validation, ETL, performance tuning, and cross-platform integrations (Salesforce, Marketing Cloud). Participate in SDLC, code reviews, data profiling, reporting, and stakeholder meetings with the goal of permanent placement after rotations.

Design, build, and deploy scalable data pipelines and schemas to ingest and normalize disparate, multi-classification data for high-fidelity simulations. Integrate APIs, manage databases and data warehouses, and maintain ETL/ELT processes to support modeling, simulation, and data science teams in mission-critical space operations.

Build and maintain data pipelines and models to provide high-quality data for reporting, BI, and analytics. Work with SQL, dbt, Python, cloud data stores, orchestration tools, and reconciliation systems to support analytics, BI tools, and data warehouse delivery.

Contribute to building and maintaining cloud-based data pipelines and data products. Develop, test, and optimize SQL and Python transformations, participate in code reviews, troubleshoot data quality issues, and follow CI/CD and documentation practices to support analytics and AI initiatives.

Build, maintain, and optimize reproducible data pipelines and large-scale relational databases for health disparities research. Collaborate with scientists to prepare, clean, transform, and integrate multi-source data, optimize pipeline performance, and produce datasets and visualizations for analysis and consortium distribution.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

Design, implement, and administer operational data flows: ingest, clean, enrich, transform, secure, and move mission-critical data. Perform exploratory data analysis, troubleshooting, and collaborate with customers to ensure compliant, reliable data pipelines.

The Snowflake Data Engineer will work on data cleansing and harmonization, moving from legacy systems to SAP S4, focusing on ETL/ELT development and view creation.

The AWS Data Engineer will work on a data cleansing and harmonization project, focusing on AWS ETL design and development using various AWS services.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

The Data Engineer will clean, manage, and analyze datasets, automate ETL processes, and collaborate with traders and software engineers to derive insights.

As a Data Engineer at MAI, you will develop and maintain data platforms, design ETL/ELT processes, ensure data quality, and collaborate with teams to optimize data utilization for analytics and ML applications.

Develop and maintain big data solutions using Hadoop, HBase, MongoDB and Core Java on Linux. Implement and support scalable data processing pipelines; contribute to big data architecture and platform tasks.

Remote entry-level Big Data Engineer role building data acquisition and munging pipelines. Requires strong Python3 (NumPy, Pandas), advanced SQL, scalable algorithm and data-structure implementation on distributed clusters, converting code to functional paradigms, and the ability to learn PySpark or Kafka quickly. Product-development, startup experience and real-world pipeline projects preferred.

Develop ETL and data visualization solutions for a big data customer and partner experience transformation program. Build native Hadoop and Vertica ETL pipelines, collaborate with stakeholders, and support data integration and visualization deliverables for analytics teams.