Software Finder

Data Engineer

Software Finder 201 District, Virginia, United States

IT Services and IT Consulting · 201-500 employees

Aug 04
data-engineer Mid (2-5 yrs) Full-time United States
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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

AWS Python SQL Apache Airflow Data Engineering ETL/ELT Data Modeling Redshift S3 Glue Lambda Athena Git Data Warehousing Business Intelligence CI/CD

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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