Vanguard
DataEngineer,Specialist
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optimal for Senior candidates.
“Data Engineer, Specialist at Vanguard. Skills: Data engineering, ETL, Data pipelines, Cloud platforms. Develop and maintain efficient ETL pipelines. Ingest, process and transform large datasets”
What You'll Achieve.
Support scalable and efficient data processing; Ensure high data quality and reliability; Provide actionable insights for business stakeholders; Meet business requirements; Improve operational efficiency
Industry & Context.
Optimize data pipelines; Improve query performance
What They're Looking For.
Must Have
8 years data analytics, programming, database administration, or data management experience, Undergraduate degree or equivalent combination of training and experience, Data modeling experience required, Proficiency in SQL, Proficiency in database technologies such as PostgreSQL, MySQL, Oracle, or SQL Server, Hands-on experience with big data frameworks like Apache Spark, Hadoop, or Databricks, Programming skills in Python, Scala, or Java for data processing and automation, Experience with cloud platforms such as AWS, Azure, or GCP, Experience in data services like AWS Glue, Redshift, Big Query, or Snowflake
Nice to Have
Graduate degree preferred
What You'll Do.
Develop and maintain efficient ETL pipelines
process and transform large datasets
Build and manage data storage solutions
Ensure high availability
performance and scalability
third-party data sources and internal
Create unified datasets
Partner with business intelligence analysts
Design and implement data-driven solutions
Design optimized data schemas and structures
Support analytical workloads
Improve query performance
Leverage orchestration tools
Automate ETL workflows
Provide technical guidance
Promote best practices
How You'll Work.
Team & Collaboration
Business intelligence analysts; Data scientists; Software engineers; Data engineering team
Full Job Description
**Role Summary** The Data Engineer, Senior Specialist is responsible for designing, developing and optimizing data pipelines and architectures to support scalable and efficient data processing. This role involves working with complex datasets, integrating multiple data sources and ensuring high data quality and reliability. **Responsibilites** 1\. Develop and maintain efficient ETL (Extract, Transform, Load) pipelines that ingest, process and transform large datasets from diverse sources. 2\. Build and manage data storage solutions using relational and non-relational databases, ensuring high availability, performance and scalability. 3\. Work with APIs, third-party data sources and internal databases to create unified datasets that provide actionable insights for business stakeholders. 4\. Partner with business intelligence analysts, data scientists and software engineers to design and implement data-driven solutions that meet business requirements. 5\. Design optimized data schemas and structures that support analytical workloads and improve query performance. 6\. Leverage orchestration tools like Apache Airflow or Prefect to automate ETL workflows and improve operational efficiency. 7\. Provide technical guidance, review code and promote best practices within the data engineering team. **Qualifications and Skills** * Minimum of eight years data analytics, programming, database administration, or data management experience. * Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred. * Data modeling experience is required. * Proficiency in SQL and database technologies such as PostgreSQL, MySQL, Oracle, or SQL Server. * Hands-on experience with big data frameworks like Apache Spark, Hadoop, or Databricks. * Strong programming skills in Python, Scala, or Java for data processing and automation. * Experience with cloud platforms such as AWS, Azure, or GCP, particularly in data services like AWS Glue, Redshift, Big Query, or
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