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- Work type
- On-site
- Location
- Cary, NC
- Posted
- 85 days ago
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- Confirmed live yesterday
- Nearby
- 99+ roles within 25 mi
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This listing doesn't post a salary. Most similar roles pay $108,250–$150,092.
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About Deutsche Bank
Deutsche Bank is a German multinational investment bank and financial services company offering corporate banking, investment banking, retail banking, asset management, and transaction banking worldwide. Industry: Investment Banking & Financial Services
Deutsche Bank currently has 53 open roles on FindRole.
Listed pay typically runs $113,599–$140,000 across 29 roles with salary data.
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TL;DR · Associate
The Associate joins the DB Global Technology team to develop and refine cloud architecture, roadmaps, standards, and best practices to support cloud adoption. The role involves designing and implementing distributed data processing pipelines with performance tuning, partitioning, and fault tolerance. Key responsibilities include building cloud-based data architectures and data lakes, creating metadata-driven ingestion frameworks, and managing enterprise data workflow orchestration. The candidate will utilize Apache Spark, Spark SQL, Spark Streaming, Apache Kafka, and REST API integrations. Technical requirements include experience with Hadoop ecosystem components like HDFS, Hive, and YARN, as well as AWS, GCP, and Azure. The role requires implementing CI/CD pipelines using Git, Jenkins, and Terraform, while integrating heterogeneous data sources including PostgreSQL, Oracle, MySQL, Parquet, JSON, and XML.
Skills
What you'll do
- Develop and refine cloud architecture roadmaps, standards, and best practices to support cloud adoption.
- Design and implement distributed data processing pipelines using Apache Spark on cloud and Hadoop platforms.
- Build cloud-based data architectures and data lakes with robust security and access controls.
- Create near-real-time and batch data pipelines using Apache Kafka and REST API integrations.
- Develop metadata-driven ingestion and transformation frameworks for reusable, configurable pipelines.
- Manage enterprise data workflow orchestration and monitoring using Airflow, Control-M, and cloud-native tools.
- Implement CI/CD pipelines and infrastructure automation using Git, Jenkins, and Terraform.
- Integrate heterogeneous enterprise data sources, relational databases, and various data storage formats.
What we're looking for
- Bachelor’s degree in Computer Engineering or a related field or equivalent.
- Three (3) years of experience designing and implementing distributed data processing pipelines using Apache Spark on cloud and Hadoop-based platforms.
- Experience developing cloud-based data architectures and data lakes with robust security and access controls.
- Experience building near-real-time and batch data pipelines with Apache Kafka and REST API integrations.
- Experience creating metadata-driven ingestion and transformation frameworks for reusable, configurable pipelines.
- Experience operating big data workloads in distributed environments using Hadoop (HDFS, Hive, YARN) and AWS/GCP/Azure.
- Experience managing enterprise data workflow orchestration using Airflow, Control-M, and cloud-native scheduling.
- Experience implementing CI/CD pipelines and Infrastructure-as-Code using Git, Jenkins, and Terraform.
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