ETL Software Engineer

3 нед. назад

90.4k–201.6k USD / годСШАHybrid

pythonetldata pipelinesrelational databases

Design, build, and optimize ETL processes and data pipelines for web-based analytics applications.

Be Challenged and Make a Difference In a world of technology, people make the difference. We believe if we invest in great people, then great things will happen. At , we provide unmatched value to our customers and employees through innovative solutions and an engaging culture. Description of Task to be Performed: We are seeking a talented and motivated ETL Engineer to design, build, and optimize high-performance data pipelines and ETL processes powering a web-based search and analytics application. This role requires the extraction, transformation, and loading of data from various sources (including relational databases and file formats), developing data adapters in Python, and fine-tuning workflows for speed and scale. This position is hybrid with one to three days per week in Chantilly VA. The position requires a Top Secret clearance and SCI eligibility with the ability to pass a CI polygraph.

Active Top Secret clearance and SCI eligibility with the ability to pass a CI polygraph.
Bachelor’s degree in computer science, Information Systems, Engineering, or related field (or equivalent experience).
5+ years of experience in data engineering, including
Building ETL/ELT pipelines
SQL query optimization
Working with relational databases such as Oracle, PostgreSQL, MySQL, or MSSQL
Experience with high level languages such as Python, Java or C#.
3+ years of experience in Python development, with a focus on ETL processes.
Experience with Elasticsearch or OpenSearch.
Experience with version control systems (e.g. GIT) and collaborative coding practices.
Experience working in an Agile Scrum environment.
Experience with scripting languages (e.g., Bash).
Experience with containerization technologies (e.g., Docker).
Experience working in Linux environments.

Knowledge of data quality, validation and monitoring frameworks, along with data governance, metadata management, and data lineage best practices.
Strong understanding of data transformation, cleansing, and normalization concepts.
Experience with data warehousing, big data frameworks, and API-based data integration from enterprise source systems.
Excellent problem-solving skills and attention to detail.