Senior Data Architect

3 weeks ago


Richmond, Virginia, United States SingleStone Full time
Senior Data Engineer

At SingleStone, we're seeking a highly skilled Senior Data Engineer to join our team. As a key member of our data engineering team, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support data analytics, business intelligence, and machine learning initiatives.

Key Responsibilities
  • Data Pipeline Development: Design, develop, and maintain scalable and reliable data pipelines that extract, transform, and load (ETL/ELT) data from various data sources.
  • Optimization and Troubleshooting: Optimize and troubleshoot data workflows for performance, scalability, and cost efficiency.
  • Automation and Monitoring: Automate and monitor data pipelines to ensure smooth, error-free data flows across environments.
  • Cloud-Based Data Architectures: Design and implement cloud-based or on-premise data architectures to support large-scale data storage and processing.
  • Collaboration and Communication: Collaborate with architects and engineering teams to ensure data systems are aligned with business objectives and technical requirements.
  • Technology Evaluation and Integration: Evaluate, select, and integrate new technologies and tools into the data stack (e.g., data lakes, data warehouses, real-time streaming technologies).
  • Data Modeling and Transformation: Design and implement complex data models that enable efficient querying and support analytics and reporting needs.
  • Data Quality and Governance: Establish and maintain best practices for data governance, including data quality controls, privacy, and security.
  • Compliance and Risk Management: Ensure compliance with data policies and regulatory standards (e.g., GDPR, CCPA).
Requirements
  • Experience: 5-7 years of experience in data engineering or software development, with a strong focus on building data pipelines and scalable infrastructure.
  • Technical Skills: Proficiency in programming languages like Python, Scala, Java, or SQL, and experience with modern data technologies such as Apache Spark, Kafka, Hadoop, or Flink.
  • Cloud Platforms: Strong knowledge of cloud platforms such as AWS, Azure, or Google Cloud, particularly their data services (e.g., AWS Redshift, Azure Data Factory, BigQuery).

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