B
Bow Wave LLC
Data Engineer 2 - TS required - Washington DC area
Skills
Google Cloud PlatformSQL QueriesLookerBig DataTableauPythonData VisualizationGoogle BigQueryAmazon RedshiftGitData AnalysisAWSTalendApache AirflowHadoopPower BIAzure
2 months ago
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Important information
Contract type:
Permanent
Salary:
$80,000 – $85,000 / year
Location:
Arrington, VA 22922, USA
Work mode:
Onsite
Published on:
21 August 2026
What they need
Education Requirement: Bachelor's Degree
Key Responsibilities:
- 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.
Required SkillsExperience
- 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 SkillsCompetencies
- 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
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