Data Architect

2 weeks ago

Bloomington, Illinois, United States Marshall Technologies Full time
Job Title: Data Engineer

Job Summary

Marshall Technologies is seeking a highly skilled Data Engineer to design, develop, and maintain scalable data systems and ensure the smooth flow of data across the organization. The ideal candidate will have a passion for building robust data infrastructure, optimizing data pipelines, and ensuring data quality.

Key Responsibilities
  • Data Pipeline Development: Design, develop, and maintain efficient data pipelines to extract, transform, and load (ETL/ELT) data from various sources into the data warehouse.
  • Data Warehousing: Develop and optimize data warehouse architecture to support advanced analytics and business intelligence requirements.
  • Data Integration: Integrate structured and unstructured data from different databases, APIs, and data lakes, ensuring smooth and efficient data transfer.
  • Database Management: Work with relational (SQL) and non-relational (NoSQL) databases to manage and query large datasets efficiently.
  • Data Quality: Implement processes for data validation, cleansing, and monitoring to ensure high data quality and consistency.
  • Collaboration: Collaborate with data scientists, analysts, and software engineers to optimize data systems and support machine learning and analytics initiatives.
  • Performance Tuning: Optimize and tune data systems for performance and scalability, ensuring quick and accurate access to large datasets.
  • Automation: Automate routine data engineering tasks, such as database backups, data ingestion, and reporting processes.
  • Security: Ensure data security and compliance with relevant regulations and industry standards, implementing encryption and access control where necessary.
Requirements
  • 4+ years of experience in data engineering, software development, or related fields.
  • Proven experience with SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra).
  • Experience with data pipeline tools such as Apache Airflow, AWS Glue, Talend, or similar.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud for data storage and processing.
  • Experience with ETL/ELT processes and tools like Apache Nifi, Apache Spark, or similar.
  • Familiarity with big data technologies (e.g., Hadoop, Hive, Spark) is a plus.
  • Strong problem-solving skills, with an ability to analyze complex data engineering challenges and implement effective solutions.
  • Experience in data modeling and data architecture design.
  • Knowledge of data governance, security, and compliance standards.
  • Strong communication skills and the ability to work in a collaborative team environment.
Preferred Qualifications
  • Experience with machine learning pipelines and supporting data scientists with feature engineering.
  • Familiarity with streaming data platforms such as Apache Kafka or Kinesis.
  • Certification in cloud platforms (AWS Certified Data Analytics, Google Cloud Data Engineer, etc.) is a plus.
  • Experience with CI/CD pipelines for data engineering workflows.
  • Experience with data visualization tools such as Tableau, Power BI, or Looker.
Education
  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.

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