Data Engineering Specialist III

Requirements

• Experience with real-time data processing and streaming architectures.
• Knowledge of data modeling techniques (Kimball, Data Vault).
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Familiarity with DevOps practices and infrastructure-as-code (Terraform, ARM, CloudFormation).
• Exposure to machine learning pipelines and feature engineering workflows.
• Certification in cloud platforms (e.g., Azure Data Engineer Associate, AWS Data Analytics).
• About AECOM
• What makes AECOM a great place to work
• As an Equal Opportunity Employer, we believe in your potential and are here to help you achieve it. All your information will be kept confidential according to EEO guidelines.

Benefits

Additional Information

May develop, construct, test, and maintain databases and large-scale processing systems. Ensures data is accessible, reliable, and efficiently processed. Combines, optimizes, and manages multiple big data sources. May be responsible for creating automated reporting systems. Provides software solutions that move data from its source to an internal database such as data warehouse. Implements data frameworks and/or architectures. Responsible for the design, development and maintenance of data pipelines to enable strong data analysis and reporting Accountable for larger portions of a project or process Utilizes a myriad of solutions to ensure problem resolution with data warehousing and data sources. Escalates unsolvable problems beyond individual knowledge and scope to senior level employees Proficient in data programming languages Knowledge of data optimization tools, data structures and architecting, data warehousing solutions Knowledge of API (application programming interface) support to allow for data access/gathering/distribution, data transformation and ELT (extract, load, transform) Utilization of algorithmic and statistical assessments, data processing tools and approaches (including AI) in support of data consumption. Required Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 2+ years of experience in data engineering or related roles. Strong programming skills in Python, Scala, or Java . Hands-on experience with SQL and relational databases. Experience designing and building data pipelines (batch and streaming) . Experience with cloud platforms (Azure, AWS, or GCP). Proficiency with big data technologies (e.g., Apache Spark, Hadoop, Kafka). Experience with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery, Synapse). Familiarity with orchestration tools (e.g., Airflow, Prefect, Dagster).

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