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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Accenture - **Location:** Suitland-Silver Hill, MD, United States - **Experience:** Experienced - **Salary:** $117,900.0 - $169,600.0 - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Confluence, JIRA, Microsoft Azure, Big Data, BigQuery, Cloud Computing, Databases, Information Engineering, Data Governance, Data Infrastructure, Data Systems, Database Queries, Distributed Systems, Python (Programming Language), PostgreSQL, Machine Learning, SQL Databases, Data Streaming, Datadog, Cloud Platform System, Snowflake, Apache Spark, Git, Kubernetes, Apache Kafka, Machine Learning Operations, Cloudwatch, Data Pipelines, Amazon Redshift, Databricks, Programming Languages - **Published:** July 16, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9033592/data-engineer ## About the Role * Programming Fundamentals: Write clean, efficient, and scalable code to build and optimize data solutions using programming languages like Python. * Data Pipeline Development: Design, build, and orchestrate robust and reliable data workflows using tools such as Apache Airflow, dbt, Prefect, or Dagster. * Cloud Platform Familiarity: Work comfortably in cloud environments, with a strong preference for experience in AWS. Experience in GCP or Azure is also highly valued. * Database & Querying Skills: Extract, integrate, and ensure the quality of data from various sources using tools and technologies such as SQL, PostgreSQL, Snowflake, Amazon Redshift, or BigQuery. * Big Data Processing: Leverage frameworks like Apache Spark, Databricks, or Apache Kafka to process and manage large-scale data workflows with reliability and efficiency. * ML Integration / MLOps: Support the implementation, deployment, and scaling of machine learning models in production environments using tools like Amazon SageMaker, MLflow, or Kubeflow. * Monitoring & Troubleshooting: Monitor data pipeline health, troubleshoot issues, and ensure data consistency using tools such as Amazon CloudWatch, Datadog, or Great Expectations. * Collaboration & Documentation: Work closely with data scientists, analysts, and other stakeholders to understand data requirements, communicate solutions, and document processes using tools like Git, Jira, and Confluence. * 2 years of experience as a Data Engineer or similar role. * Strong proficiency in Python or other programming languages relevant to data engineering. * Any additional experience with any of the following: + Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow, dbt, Prefect, Dagster). + Solid understanding of cloud platforms (AWS strongly preferred; GCP or Azure experience also considered). + Expertise in SQL and familiarity with relational and columnar databases (e.g., PostgreSQL, Snowflake, BigQuery). + Knowledge of big data processing frameworks (e.g., Apache Spark, Databricks, or Apache Kafka). + Familiarity with machine learning workflows and experience implementing MLOps tools (e.g., Amazon SageMaker, MLflow, or Kubeflow) in production environments. + Strong troubleshooting skills and experience monitoring data pipelines and system health using tools like Amazon CloudWatch, Datadog, or Great Expectations. + Excellent communication skills and a collaborative mindset, with a focus on documentation and best practices. * Experience working with large-scale distributed systems. * Knowledge of data governance and security best practices. * Proven ability to work in cross-functional teams and contribute to problem-solving and innovation. * An active TS/SCI federal security clearance is required #LI-Defense #clearancejobs ## Description We are looking for a skilled and passionate Data Engineer to join our team. You will play a critical role in designing, building, and maintaining our data infrastructure to ensure seamless data flow, scalability, and reliability. You will work closely with data scientists, analysts, and other stakeholders to develop efficient data pipelines, manage large datasets, and integrate machine learning models into production environments. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Improving quality with Agentic AI with Rovo Dev and Xray](https://www.wearedevelopers.com/videos/2005-improving-quality-with-agentic-ai-with-rovo-dev-and-xray) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [The 12 Best Jobs for Software Engineers](https://www.wearedevelopers.com/magazine/401-the-12-best-jobs-for-software-engineers)