Data Engineer
Software Finder 201 District, Virginia, United States
IT Services and IT Consulting · 201-500 employees
About the role
Design, build, and maintain scalable ETL/ELT pipelines on AWS to support business intelligence and strategic decision-making. Collaborate with the BI team to ensure data accuracy and optimize data models for performance and reliability.
What they look for
Requirements
Requires a bachelor's degree in a technical field and 2–3 years of professional experience in data or backend engineering. Candidates must possess strong SQL and Python skills, along with hands-on experience in AWS data services and workflow orchestration.
Full description
Data Engineer
Software Finder is seeking skilled and motivated Data Engineers to join its growing Data Engineering team. This AWS-focused role involves building and managing data pipelines end to end, from ingestion and transformation to delivering reliable datasets that support business intelligence, analytics, and strategic decision-making.
The ideal candidate will have strong SQL and Python skills, practical experience with AWS data services, and a solid understanding of data modeling and workflow orchestration. The data products developed in this role will support revenue-generating systems and business analytics, with opportunities to contribute to broader software engineering initiatives.
Key Responsibilities
- Design, build, deploy, and maintain scalable ETL/ELT pipelines using AWS services.
- Ingest, process, and transform data from multiple source systems into the organization’s data warehouse.
- Write, optimize, and maintain complex SQL queries for data transformation, modeling, reporting, and analytics.
- Develop reliable data models that support business intelligence dashboards, reporting, and business analysis.
- Orchestrate data workflows using Apache Airflow, AWS Step Functions, or similar technologies.
- Monitor pipeline performance and data freshness, investigate failures, and implement sustainable solutions.
- Collaborate with Business Intelligence teams to improve data accuracy, consistency, and reliability.
- Establish effective feedback loops between Data Engineering and Business Intelligence teams to address data-quality issues.
- Identify and resolve pipeline bottlenecks, data discrepancies, and recurring operational problems.
- Improve pipeline scalability, performance, observability, and cost efficiency.
- Apply data validation and quality-control practices throughout pipeline development and maintenance.
- Use AI-assisted development tools, such as Claude Code, to support development and iteration.
- Participate in code reviews and follow established software engineering and version-control standards.
- Maintain clear technical documentation for data pipelines, models, workflows, and system dependencies.
- Support broader backend and software engineering initiatives as business and team needs evolve.
- Contribute to additional data engineering and technology-related projects as required.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, Information Technology, or a related discipline.
- 2–3 years of professional experience in data engineering or a backend or software engineering role involving substantial data-related work.
- Strong SQL skills, including experience writing and optimizing complex queries.
- Proficiency in Python for data pipeline development, automation, and data processing.
- Hands-on experience with AWS data services such as Amazon S3, AWS Glue, Amazon Redshift, AWS Lambda, Amazon Athena, and Amazon EventBridge.
- Practical experience with Apache Airflow or AWS Step Functions for workflow orchestration.
- Strong understanding of data modeling fundamentals, including normalization and dimensional modeling.
- Familiarity with Git and collaborative software development workflows.
- Ability to troubleshoot data-quality issues, pipeline failures, and performance bottlenecks.
- Strong analytical, problem-solving, and cross-functional communication skills.
- Experience with dbt for SQL-based data transformation is preferred.
- Familiarity with Terraform or other infrastructure-as-code tools is preferred.
- Experience with CI/CD pipelines using GitHub Actions, AWS CodePipeline, or similar tools is preferred.
- Experience with data monitoring, observability, and pipeline cost optimization is preferred.
- Familiarity with AI coding assistants such as Claude Code is preferred.
- Understanding of data governance, validation, and quality-control practices is preferred.
- Interest in expanding into backend or broader software engineering responsibilities is preferred.
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