Data Warehouse Engineer - Intern

In a world of possibilities, pursue one with endless opportunities. Imagine Next! At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what’s possible.

Parsons is seeking a high-potential Data Engineer Graduate Intern to join our Technology and Innovation team. This role is designed for candidates with strong analytical foundations and an interest in building scalable, enterprise-grade data platforms that support operational, engineering, and executive decision-making.

• Work with frameworks like Apache Spark, Hadoop, or Apache Beam to process large datasets efficiently.
• Support development of batch and streaming data pipelines using Python and distributed processing frameworks as Apache Spark (Databricks)
• Assist in processing and transforming structured and semi-structured data at scale

• Assist in designing and implementing ETL/ELT processes for data integration and transformation.
• Contribute to the design and implementation of ETL/ELT workflows using Azure Data Factory, Databricks, or equivalent tools
• Support data ingestion from multiple sources (databases, APIs, files, cloud storage)

• Work with Azure-native data services, including:
  • Azure Data Factory
  • Azure Synapse Analytics
  • Azure Data Lake Storage (ADLS Gen2)
  • Azure Databricks
• Utilize cloud services such as Azure (Data Factory, Synapse, Data Lake), AWS (S3, Redshift, Glue), or Google Cloud Platform (Big Query, Dataflow) for data storage and processing.
• Support secure configuration of cloud resources, access controls, and data storage

• Manage and query relational databases (e.g., Postgre
  
  SQL, MySQL, Oracle) and No
  
  SQL databases (e.g., Mongo
  
  DB, Cassandra, Dynamo
  
  DB).
• Query and manage relational databases (Azure SQL, SQL Server, Postgre
  
  SQL, MySQL)
• Support analytics and reporting use cases using modern data warehouse / lakehouse architectures

• Support the development and optimization of modern data warehouse solutions like Databricks, Snowflake, Redshift, or Big Query.

• Build and manage workflows using orchestration tools like Apache Airflow, Prefect, or Luigi.
• Assist with workflow orchestration using tools such as Azure Data Factory pipelines or Apache Airflow (where applicable)
• Support scheduling, monitoring, and failure handling of data pipelines

• Work with distributed data systems and storage solutions like HDFS or cloud-native equivalents.

• Collaborate with the team using Git for code versioning and management.

• Diagnose and resolve performance issues in data systems and optimize database queries.

• Collaborate using Git-based workflows (Azure Dev Ops Repos or Git Hub)
• Support data quality checks, performance tuning, and query optimization
• Assist with documentation of data pipelines, schemas, and system design

• Proficiency in Python
  - Experience with scripting languages for automation
• Solid understanding of SQL for data querying and transformation

• Hands-on experience with Apache Spark, Hadoop, or Apache Beam
  - Familiarity with ETL/ELT processes
• Understanding of ETL / ELT concepts and data pipeline design

• Strong understanding of SQL
  
  - Experience with relational databases (Postgre
  
  SQL, MySQL, Oracle)
• Experience with No
  
  SQL databases (Mongo
  
  DB, Cassandra, Dynamo
  
  DB)

• Familiarity with Microsoft Azure data services
• Azure Data Factory
• Azure Synapse Analytics
• Azure Data Lake
• Azure Databricks
• Awareness of Azure security and identity concepts (RBAC, managed identities) is advantageous

• Experience with Databricks, Snowflake, Redshift, or Big Query

• Knowledge of tools like Apache Airflow, Prefect, or Luigi

• Experience with distributed data systems and storage solutions like HDFS

• Proficiency with Git for code versioning and collaboration

• Exposure to Azure Dev Ops or Git Hub Actions
• Familiarity with Agile / Scrum delivery environments
• Interest in enterprise analytics, cloud platforms, and data governance
• Awareness of data privacy and governance principles (e.g., GDPR concepts)
• Note:
  
  Multi-cloud exposure (AWS / GCP) is beneficial but not required. The primary environment is Microsoft Azure.
• Experience:
  
  Practical exposure to building and optimizing scalable data pipelines, batch and real-time data processing.
• Debugging:
  Familiarity with diagnosing and resolving performance issues in data systems.
• Data Governance:
  Understanding of data privacy regulations (e.g., GDPR, CCPA) and experience…