What are the responsibilities and job description for the Data Engineer 2 - TS required - Washington DC area position at Bow Wave LLC?
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 Skills & Experience
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
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 Skills & Experience
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
Salary : $80,000 - $85,000