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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer 2 - TS - **Company:** Bow Wave LLC - **Location:** Arlington, United States - **Experience:** Starter - **Contract:** Internship / Graduate position - **Skills:** Airflow, Amazon Web Services, Amazon S3, Data Analysis, Microsoft Azure, Big Data, Cloud Database, Data Validation, Extract Transform Load (ETL), Data Migration, Data Profiling, Data Visualization, Data Warehousing, Distributed Computing Environment, Document-Oriented Databases, Apache Hadoop, Python (Programming Language), Power BI, Standard Sql, Simple Data Format, SQL Databases, Tableau (Software), Talend, Workflow Management Systems, Scripting, Google Cloud, Cloud Platform System, Apache Spark, Git, Google Bigquery, Looker Analytics, Software Version Control, Data Pipelines, Amazon Redshift - **Published:** August 25, 2026 - **Apply:** https://www.dice.com/job-detail/b204265a-dc81-478c-9a9d-2944391cf57b ## About the Role 0-1 Years of Professional Experience Foundational exposure to data analysis, ETL concepts, or data migration activities-via coursework, internships, personal projects, or early professional experience. Working knowledge of SQL, including writing basic queries, joins, and aggregations. Familiarity with Python for data manipulation or automation tasks (introductory level acceptable). Introductory experience with ETL or workflow tools such as Apache Airflow, Talend, or similar platforms. Understanding of basic data warehousing concepts, such as staging, fact/dimension models, or schema structure. Exposure to cloud-based data storage or compute platforms (e.g., AWS S3/Redshift, Google BigQuery, Azure Storage). Bonus / Preferred Qualifications Hands on or coursework experience with cloud ecosystems such as AWS, Azure, or Google Cloud Platform. Exposure to big data technologies (Hadoop, Spark, or distributed processing frameworks). Familiarity with data visualization tools (Power BI, Tableau, Looker) and version control systems such as Git. Experience building or supporting automated data workflows using orchestration tools or scheduled scripting. Core Skills & Competencies Foundational ETL development and data pipeline understanding Data profiling and validation SQL and Python basics Understanding of data warehousing fundamentals Collaboration with analysts, engineers, and business stakeholders Problem solving mindset and willingness to learn Clear communication and strong documentation skills Adaptability in fast paced, evolving environments ## Description Assist in designing, developing, and maintaining basic ETL pipelines for ingesting, transforming, and loading datasets under the guidance of more experienced engineers. Support analysis of data structures, mappings, and data quality checks to identify issues or gaps. Help ensure data accuracy, consistency, and integrity by running validation queries, profiling datasets, and supporting data cleanup efforts. Contribute to data migration tasks, such as mapping source data to target systems and running migration scripts. Collaborate with analysts, data scientists, and business stakeholders to translate requirements into simple data transformations or pipeline updates. Monitor pipeline performance and assist in troubleshooting operational issues, escalating complex problems as needed. Help document data flows, transformation logic, and operational processes to support maintainability and knowledge sharing. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk)