Data Engineer

• Design, develop, and maintain scalable and reliable data pipelines for batch and real-time processing.
• Build and manage enterprise data lakes, data warehouses, and data marts.
• Develop ETL/ELT solutions using modern data engineering tools and frameworks.
• Collaborate with business stakeholders, architects, analysts, and data scientists to understand data requirements.
• Optimize data processing workflows for performance, scalability, and cost efficiency.
• Implement data quality, lineage, governance, and monitoring frameworks.
• Design and maintain data models supporting analytics and reporting use cases.
• Lead technical design discussions and provide engineering best practices.
• Troubleshoot complex data integration and performance issues.
• Mentor junior engineers and conduct code reviews.
• Support CI/CD automation and infrastructure-as-code initiatives.

• Strong experience in designing and building large-scale data platforms.
• Expertise in data warehousing and dimensional modeling.
• Experience with ETL/ELT design and implementation.
• Strong understanding of data governance, metadata management, and data quality frameworks.
• Advanced proficiency in Python and SQL.
• Experience with Spark/PySpark for large-scale data processing.
• Strong knowledge of relational and NoSQL databases.
• Experience with one or more cloud platforms such as AWS (S3, Glue, Lambda, Redshift, Athena, EMR, Step Functions) or Azure (ADF, Synapse Analytics, Databricks, ADLS Gen2).
• Experience with Big Data and Streaming technologies including Apache Spark, Kafka, or Kinesis.
• Proficiency with DevOps and Automation tools including Git, Jenkins, GitHub Actions, or Azure DevOps.
• Experience with Infrastructure as Code using Terraform or CloudFormation., * Experience with Apache Iceberg, Delta Lake, or Hudi.
• Hands-on experience with Snowflake or Databricks.
• Experience implementing Lakehouse architectures.
• Working knowledge of Data Mesh and modern data platform concepts.
• Exposure to AI/ML data pipelines and feature engineering.
• Experience in Banking, Financial Services, or Capital Markets domains.
• Experience with Hadoop ecosystem.
• Experience with Docker and Kubernetes.

Skills:

• Data Engineering.
• Python.
• SQL.
• Spark.
• PySpark.
• ETL/ELT.
• AWS.
• Azure.
• Kafka.
• Terraform.
• CI/CD.

Qualification And Education:

• 8+ years of experience in Data Engineering or related field.

Our Benefits Include:

• Medical, Dental, and Vision Insurance
• 401(k) Retirement Plan
• Health Savings Account (HSA)
• Disability Insurance (Short-Term and Long-Term)
• Life and AD&D Insurance
• Paid Sick Leave (where required by applicable state or local law)
• Supplemental Insurance Plans
• Identity Theft Protection
• Pet Insurance
• Employee Wellness Programs
• Employee Assistance Program (EAP)
• Career Growth and Professional Development Opportunities

Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia.