Data Engineer
- (SQL / Azure / Databricks) 6
- 12 Months contract
- extension McLean , VA
•
On-site M-F Job Description:
Position Summary:
We are seeking a skilled Data Engineer with 5-7 years of experience to design, build, and maintain scalable data pipelines and cloud-based data solutions. The ideal candidate will have strong expertise in SQL, Azure Data Services, and Databricks, with experience supporting analytics, reporting, and data-driven business initiatives. This role will collaborate closely with data analysts, software engineers, architects, and business stakeholders to deliver reliable, high-quality data solutions. Key Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines using Azure and Databricks. Build and optimize data ingestion processes from multiple structured and unstructured data sources. Develop and maintain data models, data warehouses, and data marts to support business intelligence and analytics needs. Write complex SQL queries, stored procedures, and performance-tuned data transformations. Implement data quality, validation, and monitoring processes to ensure data accuracy and integrity. Develop and maintain Databricks notebooks, workflows, and Spark-based data processing solutions. Collaborate with business stakeholders, analysts, and engineering teams to gather requirements and deliver data solutions. Optimize data pipelines for performance, scalability, and cost efficiency. Support production deployments, troubleshoot data issues, and perform root cause analysis. Create and maintain technical documentation, data lineage, and operational procedures.
Required Qualifications:
5-7 years of experience in Data Engineering, Data Warehousing, or related roles. Strong SQL expertise including query optimization, performance tuning, indexing, and complex data transformations. Hands-on experience with Azure Data Services including Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure SQL Database, and Azure Synapse Analytics. Strong experience with Databricks, Apache Spark, PySpark, and notebook development. Experience building and maintaining ETL/ELT pipelines in cloud environments. Proficiency in Python for data engineering and automation tasks. Experience with dimensional modeling, star/snowflake schemas, and data warehousing concepts. Knowledge of data governance, data quality, and metadata management practices. Familiarity with Git-based source control and Agile development methodologies. Strong analytical, troubleshooting, and problem-solving skills.
Preferred Qualifications:
Experience with Power BI or other reporting and visualization platforms. Knowledge of Delta Lake, Lakehouse architecture, and real-time data processing. Exposure to Azure DevOps, CI/CD pipelines, and Infrastructure-as-Code practices. Experience working with large-scale enterprise datasets and distributed data processing. Familiarity with data security, compliance, and access control best practices. Azure Data Engineer Associate (DP-203) or related cloud certifications preferred.
