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# Senior Data Engineer (SQL Server)- Arlington, VA

- **Company:** CoStar Group
- **Location:** Arlington, VA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $147,000 - $190,000
- **Contract:** Permanent contract
- **Skills:** Query Performance, Java (Programming Language), Airflow, Amazon Web Services, Amazon S3, Automation of Tests, Microsoft Azure, Big Data, Cloud Database, Cloud Engineering, Code Review, Information Systems, Computer Programming, Databases, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Warehousing, Database Storage Structures, Dimensional Modeling, Distributed Computing Environment, Amazon DynamoDB, Elasticsearch, Python (Programming Language), PostgreSQL, Machine Learning, Meta-Data Management, Microsoft SQL Server, NoSQL, Performance Tuning, Power BI, Software Engineering, SQL Stored Procedures, Data Streaming, Web Analytics, Datadog, Google Cloud, Large Language Models, Snowflake, Prompt Engineering, Apache Spark, Agentic-AI, Build Management, Information Technology, Apache Kafka, Apache Nifi, Spark Streaming, Software Version Control, Data Pipelines, Serverless Computing, Docker, Databricks
- **Published:** November 7, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-data-engineer-sql-server-arlington-va-arlington-va--6a16ca4e-b41f-446a-b9e0-fd940956d6a3

## About the Role

Microsoft SQL Server, Real Estate, Residential Real Estate, Process Improvement, Web Analytics, Industry Standards, Elasticsearch, Database Programming, Data Quality, Traceability, * Bachelor's Degree required from an accredited, not for profit, in person, university or college. Degree in Computer Science, Software Engineering, Information Systems, or a related technical field is preferred.

 * A track record of commitment to prior employers
 * 5+ years in data engineering, backend engineering, or software engineering, with a focus on data-intensive systems.
 * Advanced SQL. Strong programming skills in Python, Scala, or Java.
 * 3+ years with a relational platform such as SQL Server or PostgreSQL, including query and index tuning.
 * 2+ years building production solutions on Databricks, Spark, or an equivalent distributed processing platform.
 * Experience with dimensional modeling, data warehouse design, and data architecture.
 * Experience building and optimizing ETL/ELT pipelines for large and complex datasets.
 * Experience with an orchestration tool such as Apache Airflow or Apache NiFi in production.
 * Experience with software engineering practice: version control, automated tests, CI/CD, and code review.
 * Experience with data quality validation, performance tuning, monitoring, and production support.
 * Ability to turn business requirements into a data model and a delivery plan.
 * Clear written and verbal communication with technical and business audience.

Preferred Qualifications and Skills

 * Experience with streaming platforms such as Kafka or Spark Streaming.
 * AWS experience but experience with Azure or Google Cloud Platform is also relevant.
 * NoSQL stores such as DynamoDB, and object storage such as Amazon S3.
 * Experience with cloud-native compute, container, and serverless services.
 * Experience with data governance, metadata management, lineage, and observability tooling.
 * Experience with Docker and Kubernetes.
 * Experience with financial data under SOX, or with another regulated data domain.
 * Knowledge of Elasticsearch or a similar search platform.
 * Experience with business intelligence tools such as Power BI.
 * Experience with AI-assisted development tools and agent-based workflows.
 * Familiarity with machine learning, large language models, or prompt engineering.

## Description

* Design and build data models, data pipelines, and cloud data architecture on Databricks, Snowflake, and AWS.
 * Build and maintain high-volume ETL/ELT pipelines for analytics, operational reporting, and product features.
 * Design dimensional models and database structures that give fast and predictable query performance.
 * Tune SQL Server workloads. This includes stored procedures, execution plans, and index strategy.
 * Integrate data from internal and external sources into governed enterprise models.
 * Build data quality, lineage, testing, monitoring, and observability frameworks.
 * Optimize processing, storage, and query cost across large datasets.
 * Apply SOX and audit controls to financial data pipelines. This includes change control, access control, and evidence capture.
 * Automate data infrastructure and data collection across CoStar products.
 * Support production pipelines. Find the root cause of failures and prevent a repeat.
 * Contribute to architecture decisions, set engineering standards, and mentor other engineers.