Data Engineer

Responsibilities:

• Collaborate with data scientists, analysts, and other engineers to design and develop complex data pipelines using PySpark, Databricks, and AWS services like S3, EC2, EMR, RDS and IAM roles and policies.
• Write clean, efficient, and well-documented code that can be easily maintained and extended by the team.
• Implement new data ingestion jobs utilizing Terraform or other infrastructure as code tools to automate workflows and improve overall data processing efficiency.
• Optimize existing data pipelines for performance, scalability, and reliability using best practices in distributed computing.
• Contribute to the continuous integration and delivery of high-quality software by collaborating with team members on Agile methodologies.
• Document and maintain technical documentation related to data engineering processes, tools, and infrastructure.
• Collaborate with DevOps engineers to ensure that CI/CD pipelines are functioning effectively and efficiently, and that deployment processes are well-defined and efficient.
• Provide support for critical production systems as needed.

Qualifications:

• We are looking for a candidate with a bachelor’s degree in a technology field and 4+ years of experience in a Data Engineer role.
• 4+ years of experience working with PySpark or other distributed computing frameworks (Python preferred).
• Proficiency in Python and Scala programming languages for data engineering tasks.
• Experience with Databricks (Databricks Notebooks, workflows, Unity Catalog)
• Experience with AWS services such as S3, EC2, EMR, RDS and IAM roles and policies.
• Strong knowledge of data pipeline design and implementation, including data transformation techniques, data storage optimization, and data security best practices.
• Proficient at using version control systems like Git for managing code repositories and collaborating with team members on Agile projects.
• Familiarity with Terraform or other infrastructure as code tools for automating infrastructure deployment and configuration management.
• Experience working on Linux environments for data engineering projects, including accessing containers remotely, installing packages, managing files, services, and processes.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong problem-solving skills, ability to work independently and as part of a team, and excellent verbal and written communication skills.
• Comfortable working in a highly collaborative environment with strong attention to detail and a commitment to delivering high-quality software.
• Must be eligible for a public trust security clearance.

Nice to haves:

• Familiarity with cloud computing concepts, particularly as they apply to data engineering, is a plus.
• Experience working with other data frameworks such as Apache Hive, Apache Hadoop, or Apache Spark is a plus.
• Experience working with Alation, or other data governance tools is a plus.
• Federal consulting experience